international research excellence best paper awards 2023

Criteria for Selection Each year, the ECIS organizing committee carefully selects the Best Paper Awards based on a set of rigorous criteria. The winning papers are chosen from a pool of submissions that demonstrate originality, relevance, methodological robustness, and potential for real-world impact. The committee looks for research that addresses pressing challenges in the digital landscape, offers novel insights, and contributes significantly to the advancement of the information systems domain.

ECIS 2023 Best Paper Awardees The ECIS 2023 Best Paper Awards showcased a diverse array of research topics, reflecting the breadth and depth of the information systems field. ECIS would like to congratulate the following winners:

Best Completed Research Paper (RP)

Winner Alizadeh, Armin; Hirsch, Felix; Benlian, Alexander; Wiener, Martin; and Cram, W. Alec,  "Perceived Algorithmic Control: Conceptualization and Scale Development"  (2023). ECIS 2023 Research Papers. 353.  https://aisel.aisnet.org/ecis2023_rp/353

1st Runner-up: Lin, Yanqing; Yong, Liu; and Tuunainen, Virpi Kristiina,  "Understanding Pre-Interaction Response to Humanoid Robots: A View of Comfort with Robots"  (2023). ECIS 2023 Research Papers. 273.  https://aisel.aisnet.org/ecis2023_rp/273

2nd Runner-up: Fischer, Hannes; Wiener, Martin; and Strahringer, Susanne,  "Embarking on the Digital Transformation Journey Toward a Data-Driven Organization: Empirical Insights Into Transformation Starting Points"  (2023). ECIS 2023 Research Papers. 298.  https://aisel.aisnet.org/ecis2023_rp/298

Best Research-in-Progess Paper (RiP)

Winner Thapa, Pragyan; Thapa, Devinder; and Sæbø, Øystein,  "A Critical Perspective on Quantification of Development in ICT4D"  (2023). ECIS 2023 Research-in-Progress Papers. 67.  https://aisel.aisnet.org/ecis2023_rip/67

1st Runner-up: Li, Xiaoye; Wang, Jiancheng; Cheng, Aaron; and Fang, Qian,  "E-Commerce Live Streaming and Local Entrepreneurship: The Role of Government Officials’ Participation"  (2023). ECIS 2023 Research-in-Progress Papers. 80.  https://aisel.aisnet.org/ecis2023_rip/80

2nd Runner-up: Song, Yiliao; Cui, Tingru; and Liu, Feng,  "Designing Fair AI Systems: How Explanation Specificity Influences Users’ Perceived Fairness and Trusting Intentions"  (2023). ECIS 2023 Research-in-Progress Papers. 7.  https://aisel.aisnet.org/ecis2023_rip/7

Claudio Ciborra Award

Winner Brandwijk, Noah and de Reuver, Mark,  "Do Negative Externalities Affect Platform Membership Conditions? The Impact of Moral and Regulatory Legitimacy on Platform Governance”  (2023). ECIS 2023 Research Papers. 313.  https://aisel.aisnet.org/ecis2023_rp/313   Paper ID: 1207, presented on June 15, 14:50-16:20.

1st Runner-up: Pal, Abhipsa; De', Rahul; and Rao, H. Raghav,  "Why would microentrepreneurs continue using mobile payments? An entrepreneurial perspective with evidence from India"  (2023). ECIS 2023 Research Papers. 374.  https://aisel.aisnet.org/ecis2023_rp/374

2nd Runner-up: Schürmann, Christina Luisa; Helinski, Cindy; Koch, Julia; Westmattelmann, Daniel; and Schewe, Gerhard,  "Digital Nudging to Promote Sustainable Consumer Behavior? An Experimental Analysis in Online Fashion Retail"  (2023). ECIS 2023 Research Papers. 335.  https://aisel.aisnet.org/ecis2023_rp/335

The Best Paper Awards at ECIS not only recognize individual researchers' accomplishments but also have a broader impact on the field of information systems. These awards provide researchers with well-deserved recognition, promoting their work to a wider audience and facilitating potential collaborations with other experts in the domain.

ECIS 2024 is to be held in Paphos, Cyprus in June 2024. Please  https://ecis2024.eu/  for additional details.  Held in Europe/Africa each year, ECIS, is the first of three annual regional conferences. The Pacific Asia Conference on Information Systems (PACIS) has recently concluded and Best Paper award winners will be shared in an upcoming issue of the InSider.   The Americas Conference on Information Systems (AMCIS) will be held August 10 -12, 2023 in Panama City, Panama and virtually. Please visit  https://amcis2023.aisconferences.org/  for more information and to register. 

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Best Paper Awards 2023

Three single articles out of the “Selected Readings in Computer Graphics” of 2022 were honored with the Best Paper Award in the categories “Impact on Business”, “Impact on Society” and “Impact on Science”. A list of honorably mentioned papers consists of six more articles.

The winners in the catagories are:

Impact on Business

Boutros, Fadi; Siebke, Patrick; Klemt, Marcel; Damer, Naser; Kirchbuchner, Florian; Kuijper, Arjan

PocketNet: Extreme Lightweight Face Recognition Network Using Neural Architecture Search and Multistep Knowledge Distillation

• Presentation slides of the award ceremony

Impact on Science

Morsy Abdelkader Morsy, Mostafa; Brunton, Alan; Urban, Philipp

Shape Dithering for 3D Printing

Impact on Society

Antweiler, Dario; Sessler, David; Rossknecht, Maxim; Abb, Benjamin; Ginzel, Sebastian; Kohlhammer, Jörn

Uncovering Chains of Infections through Spatio-Temporal and Visual Analysis of COVID-19 Contact Traces

List of Publications

IPMA Global Research Awards Winners 2023

IPMA is delighted to announce the results of the IPMA Global Research Awards for 2023.

This year we received a significant number of high-quality applications, and the independent IPMA Research judges had a hard work reviewing and evaluating the submissions.

The Judges evaluated the applications based on the following criteria: Research Problem, Research Processes, Research Results, and Research People. Each submission was reviewed by 2-3 Judges independently. As a result, potential finalists were selected in each category. All judges collectively made the final ranking and decision about the winners during a final virtual meeting.

IPMA Global Research Award Winners 2023

This year, we received a significant number of high-quality applications in the IPMA Research Award category, and the final judge decided to award not one but two winners in this category.

The winners are:

Professor Giorgio Locatelli from the Politecnico di Milano, Italy, with the project “The successful planning and delivery of Megaprojects: a short and long term perspective”.

Professor Young Hoon Kwak from George Washington University, USA, with the project “Sustainable Smart City Framework for the Future”.

Congratulations to both winners and to all their colleagues involved in their research!

Graduate Research Award Winner

In the  IPMA Graduate Research Award  category, the winner is Jianfeng Zhao , PhD student from China with a PhD research titled “Rethinking value for money in Public Private Partnerships: a critique, analysis and model for infrastructure projects”.

Young Researcher Award Winner

The winner in the IPMA Young Researcher Award  category for 2023 is Ge Wang , a professor from China with research titled “Megaproject Management: Top Management Team and Governance Ecosystem”.

IPMA Global Research Achievement Award

IPMA Research Awards judges selected the IPMA Global Research Achievement Awards Winner 2023. This prestigious award was presented to Professor Anbang Qi. The Award Judges decided to reward his lifetime achievements, including research, academic and business management.

Professor Anbang Qi started his academic career in project management in 1984 when he began his project evaluation and review research. He is currently a Faculty Leader of Project Management and Evaluation at Nankai University in China, a Deputy Director of the Project Management Research Committee of China, a Deputy President of the Technological Economics Research Committee of Tianjin, and a Consultant of the Tianjin Municipal Government.

Professor Qi has received many awards and achievements, such as the IPMA Research Award 2009 for “Project Integrated Management Techniques Development and Application”, “The Special Contribution Award by PMI and China State Administration of Foreign Experts”, and he was the First Winner of the „Project Management Achievement Award by the China Project Management Research Committee“, among many other recognitions.

Professor Qi worked as a full professor at Nankai University in China and as a visiting scholar at North Carolina University in Charlotte, USA, in 1998-1999, and at the Leeds University of UK, in1990-1992,  and as a visiting trainee for Chinese University Teachers in Harvard Business School of USA, in 2004.

Congratulations once again to all winners!

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IPUMS Research Awards

The IPUMS Research Awards honor outstanding research using IPUMS data to advance or deepen our understanding of social and demographic processes. We look for papers that use innovative approaches, comparative analyses, and showcase the power of the IPUMS data collections. Cash prizes are awarded for best published work* and best graduate student work** (published or unpublished) in eight categories.

Award Categories

Each category includes an award for published work and student work (published or unpublished).

• IPUMS USA : Best paper using data from IPUMS USA (including full count data)
• IPUMS CPS : Best paper using data from IPUMS CPS
• IPUMS International : Best paper using data from IPUMS International
• IPUMS Health Surveys : Best paper using data from IPUMS NHIS and/or IPUMS MEPS
• IPUMS Spatial : Best paper using data from IPUMS NHGIS , IPUMS IHGIS , IPUMS Terra , and/or IPUMS CDOH
• IPUMS Global Health : Best paper using data from IPUMS DHS and/or IPUMS PMA (2023 and 2024 publications using the recently launched IPUMS MICS data will be eligible for next year’s competition)
• IPUMS Time Use : Best paper using data from IPUMS ATUS , IPUMS AHTUS , or IPUMS MTUS
• IPUMS Excellence in Research Award : The IPUMS mission of democratizing data demands that we increase representation of scholars from groups that are systemically excluded in research spaces. This award is an opportunity to highlight and reward outstanding work using any of the IPUMS data collections by authors who are underrepresented in social science research † . 

2023 IPUMS Research Awards Winners

Congratulations to all our winners, and thank you to everyone who submitted their work. Next year’s award process will open this coming winter.

IPUMS USA Research Awards Winners:

Published research:.

Zachary Ward Intergenerational Mobility in American History: Accounting for Race and Measurement Error

Ward's article is a major contribution to an important area of social science research. Using multiple full-count census rounds, Ward connects important measurement issues to substantive results. He argues that our understanding of trends in social mobility between 1850 and 1940 require significant revision, and that social mobility today is higher than in the past.

Student Research:

Jonathan Tollefson Environmental risk and the reorganization of urban inequality in the late 19th and early 20th century

Tollefson's paper uses creative methods to identify environmental hazards from insurance maps, showing how to enrich full-count census data on topics not covered in the census. The methods are well documented, providing a roadmap for use with other topics. Tollefson's measures of exposures to gas manufacturing show how living near environmental hazards moved from being ethnically stratified in 1880 to racially stratified in 1930. 

IPUMS CPS Research Awards Winners:

Kaitlyn M. Berry, Julia A. Rivera Drew, Patrick J. Brady, Rachel Widome Impact of smoking cessation on household food security

Berry and colleagues leverage the rotating panel and supplement features of the Current Population Survey (CPS) to examine whether reductions in cigarette use are linked to food security, thus extending a knowledge base that is primarily based on cross-sectional associations. Their results suggest that smoking cessation substantially reduces the risks of food insecurity, especially for those households with low and very low food security.

Sungbin Park, Kyung Min Lee, and John Earle Death Without Benefits: Unemployment Insurance, Re-Employment, and the Spread of Covid

Park and colleagues exploit state-level variation in the reduction of unemployment benefits during the summer of 2021 to examine the impacts on re-employment behavior across adjacent months of the Current Population Survey (CPS) between February and August of 2021 and on COVID outcomes. They find that state-level reductions in unemployment benefits both increased the likelihood of re-employment and reduced the time to re-employment, but also resulted in increased COVID cases, hospitalizations, and deaths.

IPUMS International Research Awards Winners:

Seife Dendir Intergenerational Education Mobility in Sub-Saharan Africa

This paper uses census data from 22 countries in Sub-Saharan Africa (SSA), available through IPUMS International. The author applies the intergenerational correlation method (IGC) to investigate the relationship between parents’ and children’s educational attainment across six cohorts born between the mid-1950s and early 1990s. As a whole, the SSA region had medium to high levels of educational mobility during the latter half of the twentieth century, but with worsening mobility over time. The degree of educational mobility varies widely across countries in the region, but with a narrowing gender gap across many countries. The paper demonstrates the power of census data from IPUMS International for cross-national and cross-temporal analysis. This paper is significant in its examination of developing countries that have not been studied extensively compared to their developing counterparts, and more particularly in SSA from which very little educational mobility evidence comes.

Rita Trias-Prats Gender Asymmetries in Household Headship

This paper uses IPUMS census data from 156 countries combined with global health survey data in the combined form of the CORESIDENCE database to describe female household headship on a global scale. The paper documents increasing female household headship worldwide, comparing female-headed households with male-headed households in terms of size and household composition. The paper highlights important measurement and operationalization issues by discussing assumptions built into the data collection and coding methods used to document household structure. The CORESIDENCE database and this paper showcase the breadth of IPUMS data and especially the importance of rich corresponding metadata in conducting sound methodological research.

IPUMS Health Surveys Research Awards Winners: 

Jessica Y. Ho Lifecourse Patterns of Prescription Drug Use in the United States

This work represents a novel application of demographic techniques to MEPS population-level prescribed medicine data for 1996-2019. Ho charts the historic expansion of prescribed medicine utilization in the United States, by sex and race/ethnicity, showing a dramatic increase in the simultaneous use of multiple drugs across much of the lifespan. The author attributes this dramatic change to institutional shifts in the medical and pharmaceutical industries, population aging, and long-term treatment of chronic disease.

Namgyoon Oh Nutrition to Nurturance: The Impact of Children's WIC Eligibility Loss on Parental Well-being

Combining pooled IPUMS NHIS data from 2002-14 with data on participants in the WIC supplemental nutrition program, Oh addresses a policy-relevant question about the impact of negative child-related income shocks on parental well-being. The study uses a broad range of information from NHIS, including measures of mental health, medication nonadherence, food insecurity, mortality, family income and poverty, and family relationships and finds that the negative effects of WIC loss on parental mental health are largely concentrated among single mothers.

IPUMS Spatial Research Awards Winners:

Clark Gray and Maia Call Heat and drought reduce subnational population growth in the global tropics

Gray and Call use integrated population census and climate data from IPUMS Terra for 1,809 subnational districts in 29 tropical countries to test the popular narrative that climate change will lead to depopulation of vulnerable areas. Examining intercensal periods between 1970 and 2013, they find that exposure to temperatures substantially above and/or precipitation substantially below local averages tend to depress population growth rates, but do not lead to negative population growth.

Nicolas Longuet-Marx Party Lines or Voter Preferences? Explaining Political Realignment

Longuet-Marx investigates the extent to which U.S. political realignment by education levels can be attributed separately to changes in party platforms, party discipline, voter demographics, and voter preferences. The analysis combines small-area demographic data from IPUMS NHGIS for 2000 through 2020 with precinct-level election results, all standardized to 2010 block groups. The main finding is that most of the realignment “can be attributed to changes in the supply side, in particular changes in national party positions.”

IPUMS Global Health Research Awards Winners:

Chad Hazlett, Antonio P. Ramos, and Stephen Smith Better individual-level risk models can improve the targeting and life-saving potential of early-mortality interventions

In a piece with important policy implications, the authors demonstrate that public health efforts targeting the poorest households perform little better than random targeting in reducing infant mortality rates in sub-Saharan Africa. Employing IPUMS DHS data from 22 countries and machine learning techniques, they show that using available pre-birth variables (such as the infant death of a sibling) can effectively identify the most at-risk 10 percent of infants and eliminate 15 to 30 percent of infant deaths, depending on the country.

Sara Ronnkvist, Brian Thiede, and Emma Barber Child Fostering in a Changing Climate: Evidence from Sub-Saharan Africa

Using contextual variables on temperature and precipitation, household composition data, and birth records from IPUMS DHS for 23 sub-Saharan African countries, the authors evaluate climate effects on child fostering, an under-studied aspect of climate-related migration.  Taking an admirably nuanced approach, they find that the cultural prevalence of child fostering, the number of resident biological children, and the socioeconomic status of households affect whether and how child fostering rates change in response to climate shocks. 

IPUMS Time Use Research Awards Winners:

Eunjeong Paek Workplace computerization and inequality in schedule control

Paek is resourceful in their use of data from the Current Population Survey (CPS) and the American Time Use Survey (ATUS) to examine the relationship between computer use at work and schedule control. They assemble a dataset combining CPS Work Schedule Supplement and ATUS Leave Module data along with occupational-level computerization measures from the CPS and other occupational characteristics from O*NET and find that higher educated workers benefit the most from technological advancements and computerization of work with regards to schedule control.

Anja Gruber The Impact of Job Loss on Parental Time Investment

Gruber links labor market data from the Current Population Survey (CPS) with time diary data from the American Time Use Survey (ATUS) to examine how job loss affects changes in parental time investments in children. They find that lower- and higher-income parents similarly invest their time freed up by job loss in their children, suggesting that the negative impacts of parental job loss on children (especially from low-income families) is not explained by differences in parental time investments.

IPUMS Excellence In Research Award Winners: 

Samuel H. Kye, Andrew Halpern-Manners If Residential Segregation Persists, What Explains Widespread Increases in Residential Diversity?

How can there be simultaneous improvements in neighborhood diversity but worsening residential segregation? Kye and Halpern-Manners tackle this question using block- and place-level data from IPUMS NHGIS, outlining the transformation of neighborhoods’ racial composition and the resulting place-level changes in racial segregation. The authors identify White flight as a force making neighborhoods more racially diverse, but intensifying residential segregation within larger areas.

Sophie Li The Effect of a Woman-Friendly Occupation on Employment: U.S. Postmasters Before World War II

Linking appointments of married women as postmasters from 1920-1940 to IPUMS full count census data, Li investigates how the presence of an occupation favorable to married women provided them with short-term economic gain but did not advance further employment opportunities. The paper shows an understanding of the complexities of working with historical census data and brings attention to how the interaction of economic, social, and legal factors affects women’s employment.

View past IPUMS research award winners.

• 2023 IPUMS Research Award Winners
• 2022 IPUMS Research Award Winners
• 2021 IPUMS Research Award Winners
• 2020 IPUMS Research Award Winners
• 2019 IPUMS Research Award Winners
• 2018 IPUMS Research Award Winners
• 2017 IPUMS Research Award Winners
• 2016 IPUMS Research Award Winners
• 2010-2015 IPUMS Research Award Winners

* Published research criteria stipulate use and citation of one of the eligible IPUMS data collections in a 2023 refereed publication.

** Student research award criteria stipulate use and citation of one of the eligible IPUMS data collections in a paper written in 2023 whose lead author is a student; published student work must be in a 2023 publication. We strongly encourage that unpublished research be submitted to SocArXiv, an open archive for the social sciences, or another open archive or paper repository.

† To be considered for the IPUMS Excellence in Research Award, the lead author of a paper must self-identify as belonging to one or more groups that are systemically excluded in research spaces. Because IPUMS is based in the United States, we often include persons who identify as Black/African American, Indigenous, Hispanic/Latino/a/x, Asian American, first-generation college graduates or students, LGBTQ+ persons, or persons with disabilities in our definition of systemically excluded groups. We recognize for scholars outside of the U.S., in particular, this list may not capture discrimination in their social contexts, and encourage submissions from persons who identify with a group that has been systemically excluded even if it is not explicitly listed here.  

Frode van der Laak wins 'Best Researcher Award' from the International Congress for Research Excellence

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Feb 22, 2024, 03:17 ET

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OSLO, Norway , Feb. 22, 2024 /PRNewswire/ -- In an extraordinary recognition of his pioneering research and innovations, Reltime is proud to announce that our Chief Technology Officer, Frode van der Laak , has been awarded the 'Best Researcher of the Year' award from International Congress for Research Excellence (ICRE). This prestigious accolade is in honour of his ground-breaking paper, ' Utilize 5G Mobile Handset as DAO and Node in Layer 1 Proof of Authority Blockchain .'

International Congress for Research Excellence 2024 (ICRE 24) is the renowned International Research Award given to recognize Excellence in various aspects of research & academic development. ICRE 2024 is now regarded as a benchmark of Research & Academic Excellence worldwide.

This award, bestowed by the American Chamber of Research in collaboration with the World Research Council, United Medical Council, International Journal for Science, Technology & Academic Research, Times of Research, and Chronicles Time, highlights Mr. Laak's significant contributions in the field of blockchain technology and his innovative approach of leveraging the immense computing power of 5G mobile handsets.

Mr. Laak's research stands at the forefront of integrating cutting-edge telecommunication platforms with blockchain infrastructures, paving the way for new applications, and enhancing decentralised networks' security, scalability, and efficiency.

Reltime continues to push the boundaries of what is possible in digital innovations powered by blockchain, and this award underscores our commitment to excellence and our role as leaders in the technological revolution.

International Congress for Research Excellence 2024 – ICRE 24 is a part of the Asia Research Awards (ARA) that is celebrating the research minds of the world.  The main purpose of ARA is to create a competition for raising overall performance standards and recognize the achievements of the best-performing researchers, Faculty, doctors, scientists, and scholars.

For more information about ICRE, visit https://asiaresearchawards.com/about-us/

About Reltime

Reltime is revolutionising the financial and digital services industry with its advanced Web3 platform. Reltime has developed its own Layer-1 Proof of Authority Blockchain with zero transaction and gas fees. The award-winning platform includes a range of applications such as non-custodian wallets, SuperApp, loyalty programs, payment solutions, lending services, QR codes, CBDCs and digital fiats, and utility tokens. Additionally, the Reltime platform provides customer administration features like eKYC, identity management, SLA, and reporting. By incorporating a decentralised identity, Reltime drives the next generation of digitisation in supply chain management, tokenisation, asset ownership, and global trade.

For more information about Reltime AS, visit https://www.reltime.com  

Press Contact Reltime: Bishwajit Choudhary , [email protected]  

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Announcing the NeurIPS 2023 Paper Awards 

Communications Chairs 2023 2023 Conference awards , neurips2023

By Amir Globerson, Kate Saenko, Moritz Hardt, Sergey Levine and Comms Chair, Sahra Ghalebikesabi 

We are honored to announce the award-winning papers for NeurIPS 2023! This year’s prestigious awards consist of the Test of Time Award plus two Outstanding Paper Awards in each of these three categories: 

• Two Outstanding Main Track Papers 
• Two Outstanding Main Track Runner-Ups 
• Two Outstanding Datasets and Benchmark Track Papers  

This year’s organizers received a record number of paper submissions. Of the 13,300 submitted papers that were reviewed by 968 Area Chairs, 98 senior area chairs, and 396 Ethics reviewers 3,540  were accepted after 502 papers were flagged for ethics reviews . 

We thank the awards committee for the main track: Yoav Artzi, Chelsea Finn, Ludwig Schmidt, Ricardo Silva, Isabel Valera, and Mengdi Wang. For the Datasets and Benchmarks track, we thank Sergio Escalera, Isabelle Guyon, Neil Lawrence, Dina Machuve, Olga Russakovsky, Hugo Jair Escalante, Deepti Ghadiyaram, and Serena Yeung. Conflicts of interest were taken into account in the decision process.

Congratulations to all the authors! See Posters Sessions Tue-Thur in Great Hall & B1-B2 (level 1).

Outstanding Main Track Papers

Privacy Auditing with One (1) Training Run Authors: Thomas Steinke · Milad Nasr · Matthew Jagielski

Poster session 2: Tue 12 Dec 5:15 p.m. — 7:15 p.m. CST, #1523

Oral: Tue 12 Dec 3:40 p.m. — 4:40 p.m. CST, Room R06-R09 (level 2)

Abstract: We propose a scheme for auditing differentially private machine learning systems with a single training run. This exploits the parallelism of being able to add or remove multiple training examples independently. We analyze this using the connection between differential privacy and statistical generalization, which avoids the cost of group privacy. Our auditing scheme requires minimal assumptions about the algorithm and can be applied in the black-box or white-box setting. We demonstrate the effectiveness of our framework by applying it to DP-SGD, where we can achieve meaningful empirical privacy lower bounds by training only one model. In contrast, standard methods would require training hundreds of models.

Are Emergent Abilities of Large Language Models a Mirage? Authors: Rylan Schaeffer · Brando Miranda · Sanmi Koyejo

Poster session 6: Thu 14 Dec 5:00 p.m. — 7:00 p.m. CST, #1108

Oral: Thu 14 Dec 3:20 p.m. — 3:35 p.m. CST, Hall C2 (level 1) 

Abstract: Recent work claims that large language models display emergent abilities, abilities not present in smaller-scale models that are present in larger-scale models. What makes emergent abilities intriguing is two-fold: their sharpness, transitioning seemingly instantaneously from not present to present, and their unpredictability , appearing at seemingly unforeseeable model scales. Here, we present an alternative explanation for emergent abilities: that for a particular task and model family, when analyzing fixed model outputs, emergent abilities appear due to the researcher’s choice of metric rather than due to fundamental changes in model behavior with scale. Specifically, nonlinear or discontinuous metrics produce apparent emergent abilities, whereas linear or continuous metrics produce smooth, continuous, predictable changes in model performance. We present our alternative explanation in a simple mathematical model, then test it in three complementary ways: we (1) make, test and confirm three predictions on the effect of metric choice using the InstructGPT/GPT-3 family on tasks with claimed emergent abilities, (2) make, test and confirm two predictions about metric choices in a meta-analysis of emergent abilities on BIG-Bench; and (3) show how to choose metrics to produce never-before-seen seemingly emergent abilities in multiple vision tasks across diverse deep networks. Via all three analyses, we provide evidence that alleged emergent abilities evaporate with different metrics or with better statistics, and may not be a fundamental property of scaling AI models.

Outstanding Main Track Runner-Ups

Scaling Data-Constrained Language Models Authors : Niklas Muennighoff · Alexander Rush · Boaz Barak · Teven Le Scao · Nouamane Tazi · Aleksandra Piktus · Sampo Pyysalo · Thomas Wolf · Colin Raffel

Poster session 2: Tue 12 Dec 5:15 p.m. — 7:15 p.m. CST, #813

Oral: Tue 12 Dec 3:40 p.m. — 4:40 p.m. CST, Hall C2 (level 1)  

Abstract : The current trend of scaling language models involves increasing both parameter count and training dataset size. Extrapolating this trend suggests that training dataset size may soon be limited by the amount of text data available on the internet. Motivated by this limit, we investigate scaling language models in data-constrained regimes. Specifically, we run a large set of experiments varying the extent of data repetition and compute budget, ranging up to 900 billion training tokens and 9 billion parameter models. We find that with constrained data for a fixed compute budget, training with up to 4 epochs of repeated data yields negligible changes to loss compared to having unique data. However, with more repetition, the value of adding compute eventually decays to zero. We propose and empirically validate a scaling law for compute optimality that accounts for the decreasing value of repeated tokens and excess parameters. Finally, we experiment with approaches mitigating data scarcity, including augmenting the training dataset with code data or removing commonly used filters. Models and datasets from our 400 training runs are freely available at https://github.com/huggingface/datablations .

Direct Preference Optimization: Your Language Model is Secretly a Reward Model Authors: Rafael Rafailov · Archit Sharma · Eric Mitchell · Christopher D Manning · Stefano Ermon · Chelsea Finn

Poster session 6: Thu 14 Dec 5:00 p.m. — 7:00 p.m. CST, #625

Oral: Thu 14 Dec 3:50 p.m. — 4:05 p.m. CST, Ballroom A-C (level 2)  

Abstract: While large-scale unsupervised language models (LMs) learn broad world knowledge and some reasoning skills, achieving precise control of their behavior is difficult due to the completely unsupervised nature of their training. Existing methods for gaining such steerability collect human labels of the relative quality of model generations and fine-tune the unsupervised LM to align with these preferences, often with reinforcement learning from human feedback (RLHF). However, RLHF is a complex and often unstable procedure, first fitting a reward model that reflects the human preferences, and then fine-tuning the large unsupervised LM using reinforcement learning to maximize this estimated reward without drifting too far from the original model. In this paper, we leverage a mapping between reward functions and optimal policies to show that this constrained reward maximization problem can be optimized exactly with a single stage of policy training, essentially solving a classification problem on the human preference data. The resulting algorithm, which we call Direct Preference Optimization (DPO), is stable, performant, and computationally lightweight, eliminating the need for fitting a reward model, sampling from the LM during fine-tuning, or performing significant hyperparameter tuning. Our experiments show that DPO can fine-tune LMs to align with human preferences as well as or better than existing methods. Notably, fine-tuning with DPO exceeds RLHF’s ability to control sentiment of generations and improves response quality in summarization and single-turn dialogue while being substantially simpler to implement and train.

Outstanding Datasets and Benchmarks Papers

In the dataset category : 

ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation

Authors:  Sungduk Yu · Walter Hannah · Liran Peng · Jerry Lin · Mohamed Aziz Bhouri · Ritwik Gupta · Björn Lütjens · Justus C. Will · Gunnar Behrens · Julius Busecke · Nora Loose · Charles Stern · Tom Beucler · Bryce Harrop · Benjamin Hillman · Andrea Jenney · Savannah L. Ferretti · Nana Liu · Animashree Anandkumar · Noah Brenowitz · Veronika Eyring · Nicholas Geneva · Pierre Gentine · Stephan Mandt · Jaideep Pathak · Akshay Subramaniam · Carl Vondrick · Rose Yu · Laure Zanna · Tian Zheng · Ryan Abernathey · Fiaz Ahmed · David Bader · Pierre Baldi · Elizabeth Barnes · Christopher Bretherton · Peter Caldwell · Wayne Chuang · Yilun Han · YU HUANG · Fernando Iglesias-Suarez · Sanket Jantre · Karthik Kashinath · Marat Khairoutdinov · Thorsten Kurth · Nicholas Lutsko · Po-Lun Ma · Griffin Mooers · J. David Neelin · David Randall · Sara Shamekh · Mark Taylor · Nathan Urban · Janni Yuval · Guang Zhang · Mike Pritchard

Poster session 4: Wed 13 Dec 5:00 p.m. — 7:00 p.m. CST, #105 

Oral: Wed 13 Dec 3:45 p.m. — 4:00 p.m. CST, Ballroom A-C (level 2)

Abstract: Modern climate projections lack adequate spatial and temporal resolution due to computational constraints. A consequence is inaccurate and imprecise predictions of critical processes such as storms. Hybrid methods that combine physics with machine learning (ML) have introduced a new generation of higher fidelity climate simulators that can sidestep Moore’s Law by outsourcing compute-hungry, short, high-resolution simulations to ML emulators. However, this hybrid ML-physics simulation approach requires domain-specific treatment and has been inaccessible to ML experts because of lack of training data and relevant, easy-to-use workflows. We present ClimSim, the largest-ever dataset designed for hybrid ML-physics research. It comprises multi-scale climate simulations, developed by a consortium of climate scientists and ML researchers. It consists of 5.7 billion pairs of multivariate input and output vectors that isolate the influence of locally-nested, high-resolution, high-fidelity physics on a host climate simulator’s macro-scale physical state. The dataset is global in coverage, spans multiple years at high sampling frequency, and is designed such that resulting emulators are compatible with downstream coupling into operational climate simulators. We implement a range of deterministic and stochastic regression baselines to highlight the ML challenges and their scoring. The data (https://huggingface.co/datasets/LEAP/ClimSim_high-res) and code (https://leap-stc.github.io/ClimSim) are released openly to support the development of hybrid ML-physics and high-fidelity climate simulations for the benefit of science and society.   

In the benchmark category :

DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Authors: Boxin Wang · Weixin Chen · Hengzhi Pei · Chulin Xie · Mintong Kang · Chenhui Zhang · Chejian Xu · Zidi Xiong · Ritik Dutta · Rylan Schaeffer · Sang Truong · Simran Arora · Mantas Mazeika · Dan Hendrycks · Zinan Lin · Yu Cheng · Sanmi Koyejo · Dawn Song · Bo Li

Poster session 1: Tue 12 Dec 10:45 a.m. — 12:45 p.m. CST, #1618  

Oral: Tue 12 Dec 10:30 a.m. — 10:45 a.m. CST, Ballroom A-C (Level 2)

Abstract: Generative Pre-trained Transformer (GPT) models have exhibited exciting progress in capabilities, capturing the interest of practitioners and the public alike. Yet, while the literature on the trustworthiness of GPT models remains limited, practitioners have proposed employing capable GPT models for sensitive applications to healthcare and finance – where mistakes can be costly. To this end, this work proposes a comprehensive trustworthiness evaluation for large language models with a focus on GPT-4 and GPT-3.5, considering diverse perspectives – including toxicity, stereotype bias, adversarial robustness, out-of-distribution robustness, robustness on adversarial demonstrations, privacy, machine ethics, and fairness. Based on our evaluations, we discover previously unpublished vulnerabilities to trustworthiness threats. For instance, we find that GPT models can be easily misled to generate toxic and biased outputs and leak private information in both training data and conversation history. We also find that although GPT-4 is usually more trustworthy than GPT-3.5 on standard benchmarks, GPT-4 is more vulnerable given jailbreaking system or user prompts, potentially due to the reason that GPT-4 follows the (misleading) instructions more precisely. Our work illustrates a comprehensive trustworthiness evaluation of GPT models and sheds light on the trustworthiness gaps. Our benchmark is publicly available at https://decodingtrust.github.io/.

Test of Time

This year, following the usual practice, we chose a NeurIPS paper from 10 years ago to receive the Test of Time Award, and “ Distributed Representations of Words and Phrases and their Compositionality ” by Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg Corrado, and Jeffrey Dean, won. 

Published at NeurIPS 2013 and cited over 40,000 times, the work introduced the seminal word embedding technique word2vec. Demonstrating the power of learning from large amounts of unstructured text, the work catalyzed progress that marked the beginning of a new era in natural language processing.

Greg Corrado and Jeffrey Dean will be giving a talk about this work and related research on Tuesday, 12 Dec at 3:05 – 3:25 pm CST in Hall F.  

Related Posts

2023 Conference

Announcing NeurIPS 2023 Invited Talks

Reflections on the neurips 2023 ethics review process, neurips newsletter – november 2023.

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• The decision of the evaluation panel is final and binding.
• The personal information collected during the award nomination process will be used solely for the purpose of processing nominations and communicating with nominees.
• For more details, please refer to our Privacy Policy.

6. Announcement of Winners

• The announcement of award winners will be made on our official website within the specified time frame.
• Winners will also be notified via email or other contact information provided during the nomination process.

7. Awards Ceremony

• Winners may be invited to participate in an awards ceremony or event to receive their recognition.

8. Award Usage

• Award winners are encouraged to use their recognition for promotional and professional purposes, with appropriate acknowledgment.

9. Changes to Terms & Conditions

• We reserve the right to make changes or updates to these Terms & Conditions as necessary.
• Any changes will be communicated to nominees through the official website or other means.

10. Disqualification

• We reserve the right to disqualify nominations that do not comply with the Terms & Conditions or submission guidelines.

11. Liability

• We are not liable for any errors or inaccuracies in the award nomination process.
• We are not responsible for any technical issues or disruptions that may affect the submission process.

12. Contact Information

• For inquiries or assistance related to award nominations, please contact us at [email protected]

By participating in the award nomination process, you agree to abide by these Terms & Conditions. Failure to comply with these terms may result in the disqualification of your nomination.

Privacy Policy

Privacy Policy for Award Nomination

1. Information Collection

We collect the following information during the award nomination process:

• Personal Information:  This includes your name, email address, affiliation, contact details, and any additional information required for nomination.
• Submission Data:  Information related to your award nomination, including the content of your submission and any supporting materials.
• Usage Information:  We may collect data about your interactions with our nomination platform, including IP addresses and device information.

2. Use of Information

We use the information you provide during award nomination for the following purposes:

• To process your award nomination and communicate with you regarding your submission.
• To send updates and notifications related to the award nomination process.
• To evaluate award nominations and select winners.
• To improve and analyze our award nomination platform.

3. Data Sharing and Disclosure

We do not share your personal information with third parties, except for the purposes of managing the award nomination process.

4. Data Security

We take reasonable measures to safeguard your personal information from unauthorized access, disclosure, alteration, or destruction.

5. Your Choices

You have the right to:

• Review and update your personal information.
• Opt-out of receiving award-related communications.
• Request the deletion of your personal information, subject to legal requirements.

6. Cookies and Tracking Technologies

We may use cookies and similar technologies to enhance your experience on our award nomination platform. You can manage cookie preferences through your browser settings.

7. Changes to This Privacy Policy

We may update this Privacy Policy as necessary. Any significant changes will be communicated to you.

8. Contact Information

If you have questions or concerns about your privacy or this Privacy Policy, please contact us at [email protected]

9. Terms & Conditions

Please note that by participating in the award nomination process, you agree to our Terms & Conditions. To review our Terms & Conditions, please visit website.

10. Responsibility

Delegates are personally responsible for the accuracy and authenticity of the information provided during the award nomination process.

11. Disclaimer

All award nominations are subject to review and evaluation. Nominees are responsible for the accuracy and authenticity of their submissions.

Publication-Based Awards

Publication-Based Awards Explanation:

Publication-based awards are a category of recognition within the "International Research Excellence and Citation Awards" that specifically acknowledge and honor outstanding contributions to the field made through published research, papers, or publications. These awards are designed to celebrate the significant impact of scholarly work and its contribution to the advancement of Citation Awards

Key Components of Publication-Based Awards:

• To be eligible for publication-based awards, nominees must have authored or co-authored research papers, articles, or publications related to Citation Awards.
• The publications must be relevant to the field and have been published within a specific time frame, typically within the last [number] years.
• Nominees or their peers can submit publications for consideration in this award category.
• The nomination process may require submitting the publication title, authors, publication date, and a brief summary of the research's significance and impact.
• A panel of expert judges or evaluators with expertise in Citation Awards will review the nominated publications.
• The evaluation process considers factors such as the quality of research, innovation, impact on the field, and contribution to solving real-world problems.
• Publications that meet the criteria and are selected by the judging panel may receive awards or recognition during the award ceremony.
• Winning publications are typically acknowledged for their excellence and impact on the field.
• Recognition: Winners of publication-based awards gain recognition and credibility in the academic and research communities.
• Networking: Award ceremonies and events provide opportunities for networking and collaboration with peers.
• Career Advancement: Such awards can enhance the professional reputation of researchers and open up new career opportunities.
• Publication-based awards encourage researchers and scholars to publish high-quality work and contribute to the dissemination of knowledge in the field.
• They promote excellence in research and innovation in Citation Awards.
• The selection process for publication-based awards is typically transparent and conducted by a panel of experts, ensuring fairness and impartiality.
• There may be multiple publication-based award categories, such as Best Research Paper, Best Journal Article, Best Conference Presentation, etc., each with its specific criteria.

Publication-based awards serve as a way to acknowledge the critical role that research plays in advancing the field of Citation Awards. They motivate researchers to produce impactful work and contribute to the ongoing growth and development of the discipline.

Awards Categories

• Most Cited Article Awards
• Most Reader's Article Awards
• Most Commended Article Awards
• Most Liked Article Awards
• Most Shared Article Awards
• Most Tweeted Article Awards
• Most Cited Author Awards
• Fast Cited Article Awards
• Best Paper Awards
• Best Researcher Awards
• Best Review Article Awards
• Best Research Article Awards
• Strategic Business Citation Leadership Award
• Global Citation Leadership Achievement Award
• Academic and Business Citation Visionary Award
• Industry-Driven Citation Excellence Award
• Citation Mastery for Innovation Award
• Academic and Business Citation Vanguard Award
• Interdisciplinary Citation Impact Award
• Collaborative Citation Excellence Award
• Citation Frontier in Business and Research Award
• Academic and Industry Integration Citation Award
• Innovative Practices Citation Achievement Award
• Citation Excellence in Research and Business Award
• Academic and Industrial Citation Trailblazer Award
• Cross-disciplinary Citation Innovation Award
• Strategic Citation Leadership Excellence Award
• Research and Business Citation Pioneer Award
• Academic and Industry Citation Mastery Award
• Innovation Catalyst Citation Award
• Global Citation Impact Achievement Award
• Business and Academic Citation Innovator Award
• Citation Excellence Across Industries Award
• Citation Trailblazer in Research and Innovation Award
• Innovative Business Citation Pioneer Award
• Academic Excellence Citation Award
• Research Citation Vanguard Award
• Citation Achievement in Business Leadership Award
• Innovation in Citation Practices Award
• Business Citation Trailblazer Award
• Academic Citation Influence Award
• Research and Innovation Citation Excellence Award
• Citation Visionary in Industry Award
• Academic Citation Impact Award
• Innovation Citation Catalyst Award
• Citation Mastery in Business Achievement Award
• Research Citation Excellence Award
• Outstanding Industrial Citation Innovation Award
• Academic Citation Trailblazer Award
• Citation Pioneer Award for Business Excellence
• Innovative Citation Leadership Award
• Excellence in Citation Achievement Award

Awards & Recognitions

• Papers presented at the conference or journal may be eligible for this award.
• The paper should demonstrate outstanding quality and contribution to the respective field.
• This award acknowledges excellence in paper presentations at the conference.
• The paper should have received a high number of citations, indicating
• This award recognizes papers that have made a substantial impact in their respective areas.
• Best Researcher Award:
• Working professionals can nominate individuals.
• Nominees must be under 45 years of age as of the conference date.
• Nominees must have a proven track record of significant research contributions, including collaborations, contracts, and publications.
• This award celebrates individuals who have made outstanding contributions to their field of expertise.

Subject Tracks

• Track 1:Agricultural and Biological Sciences
• Track 2: Arts and Humanities
• Track 3: Biochemistry
• Track 4:Genetics and Molecular Biology
• Track 5: Business
• Track 6: Management and Accounting
• Track 7: Chemical Engineering
• Track 8: Chemistry
• Track 9: Computer Science
• Track 10: Decision Sciences
• Track 11:Earth and Planetary Sciences
• Track 12: Economics
• Track 13: Econometrics and Finance
• Track 14: Energy
• Track 15:Engineering
• Track 16: Environmental Science
• Track 17: Immunology and Microbiology
• Track 18: Materials Science
• Track 19:Mathematics
• Track 20: Medicine and Dentistry
• Track 21: Neuroscience
• Track 22: Nursing and Health Professions
• Track 23: Pharmacology
• Track 24: Toxicology and Pharmaceutical Science
• Track 25: Physics and Astronomy
• Track 26: Psychology
• Track 27: Social Sciences
• Track 28: Veterinary Science and Veterinary Medicine

What are the International Research Excellence and citation Awards?

The international Research Excellence and citation Awards is an esteemed recognition program that celebrates excellence and innovation in the fields of Citation Awards, particularly based on outstanding publications

Who can nominate or apply for these awards?

The awards are open to both individuals and organizations worldwide who have made significant contributions to the field of Citation Awards through exceptional publications.

What categories or criteria are included in the awards?

The awards feature various categories that encompass a wide range of achievements and contributions to Citation, primarily focusing on outstanding publications. The specific criteria for each category can be found on our website.

How do I submit a nomination or application?

Nominations and applications, which include outstanding publications, can be submitted through our website. Please visit [ Website URL ] for detailed submission guidelines and deadlines.

Can I nominate myself or my own organization?

Yes, self-nominations and nominations for your own organization are welcome.

What is the evaluation process for the nominations?

Nominations, including publications, are evaluated by a distinguished panel of experts in the field of Citation. They assess nominees based on the criteria outlined on our website.

When will the winners be announced?

• The announcement of award winners, including the publication-based awards, will be displayed on our website within less than 10 days after the nomination. Additionally, the winners will be honored at our annual award ceremony. Please refer to our website for the event date and detail

What are the benefits of winning an award in Citation?

Winning an award in Citation, especially for outstanding publications, provides recognition and credibility for your research and contributions in the industry. It can also open up networking and collaboration opportunities.

Are there any previous winners or success stories from these awards?

You can find information about past award winners and their success stories, including their outstanding publications, on our website.

Can I contact the organizers for further information or assistance?

If you have any questions or need assistance, please feel free to reach out to our support team through the contact information provided on our website.

What is the significance of these awards in the Citation industry?

These awards are highly regarded in the industry and serve as a prestigious recognition of excellence and innovation in the field of Citation, particularly based on outstanding publications.

Is there an awards ceremony or event associated with the program?

Yes, there is an awards ceremony where the winners, including those recognized for their publications, will be honored. Details about the ceremony can be found on our website.

Are there any restrictions on the geographic location of nominees?

There are no geographic restrictions; nominations, especially those based on outstanding publications, are open to individuals and organizations worldwide.

What are the judging criteria for the awards?

The judging criteria are based on various factors, including the quality and impact of publications, innovation, and contributions to the advancement of Citation. Detailed criteria are available on our website.

Tips for a Successful Nomination

• Before submitting a nomination, carefully review the available award categories to ensure you are applying for the most suitable one that aligns with your work or contributions.
• Familiarize yourself with the submission guidelines and eligibility criteria for the specific award category you intend to apply for.
• Craft a well-structured nomination that highlights the significance and impact of your contributions to the field of Citation Awards.
• Clearly articulate the problem you addressed, the methodology you employed, and the results achieved.
• Include any relevant supporting materials, such as research papers, project reports, or evidence of innovations, to strengthen your nomination.
• Ensure that all information provided in your nomination is accurate and authentic. Any attempt to provide false or misleading information may result in disqualification.
• If you are submitting for a publication-based award, make sure the nominated publication(s) meet the specified criteria and are directly related to Citation Awards.
• Provide accurate contact information to ensure you can be reached for updates, notifications, and further communication related to your nomination.
• Carefully proofread and edit your submission for clarity, coherence, and correctness. A well-presented nomination enhances your chances of being recognized.
• Emphasize the real-world impact of your work and any innovative aspects that distinguish your contributions from others.
• If the nomination process requires recommendation letters or endorsements, ensure that they are provided by reputable sources who can speak to the quality and significance of your work.
• Submit your nomination well before the deadline to avoid any last-minute technical issues or delays.
• Consider networking with peers and experts in the field of Citation Awards. Building professional relationships can lead to valuable endorsements and support for your nomination.
• If you are selected as a winner, make plans to attend the award ceremony or event to receive your recognition and connect with fellow professionals in the field.
• Study the profiles and submissions of past award winners to understand what made their nominations successful.
• If your nomination is not successful, consider seeking feedback from the award organizers or evaluators to improve your future nominations.

Oluwaseun Samuel Olabode receives second runner-up Best Paper Award at 2024 ASCE i3CE conference - Lyles School of Civil and Construction Engineering - Purdue University

Oluwaseun Samuel Olabode receives second runner-up Best Paper Award at 2024 ASCE i3CE conference

Construction Engineering Ph.D. student Oluwaseun Samuel Olabode has received the second runner-up Best Paper Award at the 2024 ASCE International Conference on Computing in Civil Engineering (i3ce2024), held at Carnegie Mellon University in Pittsburgh, PA.

The paper, "Automaticity Diagnosis in Construction: A Longitudinal Study Using Attentional Measures," presents research conducted in collaboration with Behzad Esmaeili, Associate Professor of Civil Engineering and Industrial Engineering, and Oluwaseun's advisor. This manuscript is part of a larger study that pioneers the application of automaticity theory into the construction industry. The overall goal of the study is to examine methods that are indicative of the development of automaticity on construction sites and its implications on construction safety and productivity.

2023 TiiS Best Paper announcement

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