Sat 12:00 a.m. - 12:10 a.m.
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Introduction and opening remarks
(
Intro
)
>
SlidesLive Video
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Arpit Agarwal · Maximilian Nickel · Tina Eliassi-Rad · Hoda Heidari · Nicolas Usunier · Alessandro Lazaric
🔗
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Sat 12:10 a.m. - 12:40 a.m.
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Inequality and Fairness in social networks and algorithms
(
Invited Talk
)
>
SlidesLive Video
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Fariba Karimi
🔗
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Sat 12:40 a.m. - 1:10 a.m.
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Sociotechnical Safety Evaluation of AI systems
(
Invited Talk
)
>
SlidesLive Video
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Laura Weidinger
🔗
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Sat 1:10 a.m. - 1:30 a.m.
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Update from UK Gov's AI Safety Institute - Evals & Advancing AI Governance
(
Invited Talk
)
>
SlidesLive Video
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Cozmin Ududec
🔗
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Sat 1:30 a.m. - 2:30 a.m.
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Poster Session (with coffee break)
(
Poster Session
)
>
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🔗
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Sat 2:30 a.m. - 3:00 a.m.
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Causal Inference from Competing Treatments
(
Invited Talk
)
>
SlidesLive Video
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Ana-Andreea Stoica
🔗
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Sat 3:00 a.m. - 3:15 a.m.
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Contributed Talk: Generative AI Misuse: A Taxonomy of Tactics and Insights from Media Data
(
Contributed Talk
)
>
SlidesLive Video
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🔗
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Sat 3:15 a.m. - 3:30 a.m.
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Contributed Talk: Models That Prove Their Own Correctness
(
Contributed Talk
)
>
SlidesLive Video
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🔗
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Sat 3:30 a.m. - 5:00 a.m.
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Lunch (provided by venue)
(
Lunch
)
>
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🔗
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Sat 5:00 a.m. - 5:30 a.m.
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User Dynamics in Machine Learning Systems
(
Invited Talk
)
>
SlidesLive Video
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Sarah Dean
🔗
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Sat 5:30 a.m. - 6:00 a.m.
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Optimizing Interventions for Social Impact: A Multi-Armed Bandit Approach to Public Health
(
Invited Talk
)
>
SlidesLive Video
|
Milind Tambe
🔗
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Sat 6:00 a.m. - 6:30 a.m.
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Human expertise in algorithmic prediction
(
Invited Talk
)
>
SlidesLive Video
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Manish Raghavan
🔗
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Sat 6:30 a.m. - 8:00 a.m.
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Poster Session (with coffee break)
(
Poster Session
)
>
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🔗
|
-
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Limits to Predicting Online Speech Using Large Language Models
(
Poster
)
>
link
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Mina Remeli · Moritz Hardt · Robert C. Williamson
🔗
|
-
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Artificial Generational Intelligence: Cultural Accumulation in Reinforcement Learning
(
Poster
)
>
link
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Jonathan Cook
🔗
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-
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Designing Experimental Evaluations of Algorithmic Interventions with Human Decision Makers In Mind
(
Poster
)
>
link
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Inioluwa Raji · Lydia T. Liu
🔗
|
-
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Risk Scores in Algorithmic Decision-Making as Statistical Fatalism
(
Poster
)
>
link
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Sebastian Zezulka · Konstantin Genin
🔗
|
-
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Learning Graph Neural Networks from Biased Outcome Data
(
Poster
)
>
link
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Sidhika Balachandar · Shuvom Sadhuka · Bonnie Berger · Emma Pierson · Nikhil Garg
🔗
|
-
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A Baseline that Matters: Categorical Prioritization as Benchmark for Social Policy Algorithms
(
Poster
)
>
link
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Benedikt Stroebl · Rajiv Swamy · Lydia T. Liu
🔗
|
-
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A Generative Port of Mars
(
Poster
)
>
link
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Oliver Slumbers · Joel Z Leibo · Marco Janssen
🔗
|
-
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Improving Centrality Fairness in Algorithmic Link-Recommendations
(
Poster
)
>
link
|
Madhura Pawar · Fariba Karimi · Fernando Santos
🔗
|
-
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Stochastic Concept Bottleneck Models
(
Poster
)
>
link
|
Moritz Vandenhirtz · Sonia Laguna · Ričards Marcinkevičs · Julia Vogt
🔗
|
-
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Why Would You Suggest That? Human Trust in Language Model Responses
(
Poster
)
>
link
|
Manasi Sharma · Ho Chit Siu · Rohan Paleja · Jaime D Pena
🔗
|
-
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Mitigating Exposure Biases in Personalized Timelines through Agent-based Models
(
Poster
)
>
link
|
Nathan Bartley · Keith Burghardt · Kristina Lerman
🔗
|
-
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Learning the eye of the beholder: Statistical modeling and estimation for personalized color perception
(
Poster
)
>
link
|
Xuanzhou Chen · Austin Xu · Jingyan Wang · Ashwin Pananjady
🔗
|
-
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Strategic Linear Contextual Bandits
(
Poster
)
>
link
|
Thomas Kleine Buening · Aadirupa Saha · Christos Dimitrakakis · Haifeng Xu
🔗
|
-
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The Role of Learning Algorithms in Collective Action
(
Poster
)
>
link
|
Omri Ben-Dov · Jake Fawkes · Samira Samadi · Amartya Sanyal
🔗
|
-
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Optimizing Machine Learning Explanations for Properties
(
Poster
)
>
link
|
Hiwot Belay Tadesse · Yaniv Yacoby · Weiwei Pan · Finale Doshi-Velez
🔗
|
-
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Is a Good Description Worth a Thousand Pictures? Reducing Multimodal Alignment to Text-Based, Unimodal Alignment
(
Poster
)
>
link
|
Amin Memarian · Touraj Laleh · Irina Rish · Ardavan S. Nobandegani
🔗
|
-
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Predictive Performance Comparison of Decision Policies Under Confounding
(
Poster
)
>
link
|
Luke Guerdan · Amanda Coston · Ken Holstein · Steven Wu
🔗
|
-
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To Give or Not to Give? The Impacts of Strategically Withheld Recourse
(
Poster
)
>
link
|
Yatong Chen · Andrew Estornell · Yevgeniy Vorobeychik · Yang Liu
🔗
|
-
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Post-processing fairness with minimal changes
(
Poster
)
>
link
|
Federico Di Gennaro · Thibault Laugel · Vincent Grari · Xavier Renard · Marcin Detyniecki
🔗
|
-
|
"You just can’t go around killing people'' Explaining Agent Behavior to a Human Terminator
(
Poster
)
>
link
|
Uri Menkes · Ofra Amir · Assaf Hallak
🔗
|
-
|
Bias Transmission in Large Language Models: Evidence from Gender-Occupation Bias in GPT-4
(
Poster
)
>
link
|
Kirsten Morehouse · Weiwei Pan · Juan Manuel Contreras · Mahzarin Banaji
🔗
|
-
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Machine Learning Without True Probabilities
(
Poster
)
>
link
|
Benedikt Höltgen · Robert C. Williamson
🔗
|
-
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Evaluating Fairness in Black-box Algorithmic Markets: A Case Study of Ride Sharing in Chicago
(
Poster
)
>
link
|
Yuhan Liu · Yuhan Zheng · Siyuan Zhang · Lydia T. Liu
🔗
|
-
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CoBo: Collaborative Learning via Bilevel Optimization
(
Poster
)
>
link
|
Diba Hashemi · Lie He · Martin Jaggi
🔗
|
-
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Bayesian Collaborative Bandits for Time Slot Inference in Maternal Health Programs
(
Poster
)
>
link
|
Arpan Dasgupta · Arun Sai Suggala · Karthikeyan Shanmugam · Aparna Taneja · Milind Tambe
🔗
|
-
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User-Creator Feature Dynamics in Recommender Systems with Dual Influence
(
Poster
)
>
link
|
Tao Lin · Kun Jin · Andrew Estornell · Xiaoying Zhang · Yiling Chen · Yang Liu
🔗
|
-
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The Limitations of Model Retraining in the Face of Performativity
(
Poster
)
>
link
|
Anmol Kabra · Kumar Kshitij Patel
🔗
|
-
|
Nearly-tight Approximation Guarantees for the Improving Multi-Armed Bandits Problem
(
Poster
)
>
link
|
Avrim Blum · Kavya Ravichandran
🔗
|
-
|
Bridging the Gap between AI Developers and Social Practitioners: A Fairness Framework for Designing AI Systems
(
Poster
)
>
link
|
MÍRIAN FRANCIELLE DA SILVA · Mariano Beiró · Marisa Vasconcelos · Ana Couto
🔗
|
-
|
Conformal Prediction Sets Improve Human Decision Making
(
Poster
)
>
link
|
Jesse Cresswell · yi sui · Bhargava Kumar · Noël Vouitsis
🔗
|
-
|
Challenging the Human-in-the-loop in Algorithmic Decision-making
(
Poster
)
>
link
|
Sebastian Tschiatschek · Eugenia Stamboliev · Timothée Schmude · Mark Coeckelbergh · Laura Koesten
🔗
|
-
|
From Individual Experience to Collective Evidence: An Incident-Based Framework for Identifying Systemic Discrimination
(
Poster
)
>
link
|
Jessica Dai · Paula Gradu · Inioluwa Raji · Benjamin Recht
🔗
|
-
|
Causal models predict average outcomes, not individual effects
(
Poster
)
>
link
|
Benedikt Höltgen · Robert C. Williamson
🔗
|
-
|
What is the Right Notion of Distance between Predict-then-Optimize Tasks?
(
Poster
)
>
link
|
Paula Rodriguez-Diaz · Kai Wang · David Alvarez-Melis · Milind Tambe
🔗
|
-
|
The Missing Link: Allocation Performance in Causal Machine Learning
(
Poster
)
>
link
|
Unai Fischer Abaigar · Christoph Kern · Frauke Kreuter
🔗
|
-
|
Controlling Counterfactual Harm in Decision Support Systems Based on Prediction Sets
(
Poster
)
>
link
|
Eleni Straitouri · Suhas Thejaswi · Manuel Gomez-Rodriguez
🔗
|
-
|
A Sim2Real Approach for Identifying Task-Relevant Properties in Interpretable Machine Learning
(
Poster
)
>
link
|
Eura Nofshin · Esther Brown · Brian Lim · Weiwei Pan · Finale Doshi-Velez
🔗
|
-
|
Adaptive Algorithmic Interventions for Escaping Pessimism Traps in Dynamic Sequential Decisions
(
Poster
)
>
link
|
Emily Diana · Alexander Tolbert · Kavya Ravichandran · Avrim Blum
🔗
|
-
|
Smooth Ambiguity-Averse Preferences and Bayesian Nonparametrics for Data-Driven Distributionally Robust Optimization
(
Poster
)
>
link
|
Nicola Bariletto · Nhat Ho
🔗
|
-
|
From Unknown to Known: An AI Coaching Problem in Open-World Environments
(
Poster
)
>
link
|
Xuejie Liu · Anji Liu · Zihao Wang · Xinyue Zheng · Liwen Zhu · Haobo Fu · Yitao Liang
🔗
|
-
|
Reconciling Predictive Multiplicity in Practice
(
Poster
)
>
link
|
Tina Behzad · Sílvia Casacuberta · Emily Diana · Alexander Tolbert
🔗
|
-
|
The Impact of Recommender Systems and Homophily in Information Diffusion on Online Social Media
(
Poster
)
>
link
|
João Fonseca · Fernando Santos
🔗
|
-
|
Measuring Fairness in Large-Scale Recommendation Systems with Missing Labels
(
Poster
)
>
link
|
Yulong Dong · Kun Jin · Xinghai Hu · Yang Liu
🔗
|
-
|
Do causal predictors generalize better to new domains?
(
Poster
)
>
link
|
Vivian Y. Nastl · Moritz Hardt
🔗
|
-
|
AnonFair: A Flexible Toolkit for Algorithmic Fairness
(
Poster
)
>
link
|
Eoin Delaney · Zihao Fu · Sandra Wachter · Brent Mittelstadt · Chris Russell
🔗
|
-
|
When Does Homogenization Reduce Competition in Algorithmic Personalized Pricing?
(
Poster
)
>
link
|
Nathan Jo · Ashia Wilson · Kathleen A. Creel · Manish Raghavan
🔗
|
-
|
Fairness in Ranking under Disparate Uncertainty
(
Poster
)
>
link
|
Richa Rastogi · Thorsten Joachims
🔗
|
-
|
Models That Prove Their Own Correctness
(
Poster
)
>
link
|
Noga Amit · Shafi Goldwasser · Orr Paradise · Guy Rothblum
🔗
|
-
|
Exploring Desiderata for Individual Fairness
(
Poster
)
>
link
|
Shai Ben-David · Tosca Lechner · Ruth Urner
🔗
|
-
|
Attaining Human's Desirable Outcomes in Human-AI Interaction via Structural Causal Games
(
Poster
)
>
link
|
Anjie Liu · Jianhong Wang · Haoxuan Li · Xu Chen · Jun Wang · Samuel Kaski · Mengyue Yang
🔗
|
-
|
Uncertainty-Aware Fair Regularization Under Datasets With Incomplete Sensitive Information
(
Poster
)
>
link
|
Andreas Athanasopoulos · Christos Dimitrakakis
🔗
|
-
|
Privacy-Efficacy Tradeoff of Clipped SGD with Decision-dependent Data
(
Poster
)
>
link
|
Qiang Li · Michal Yemini · Hoi To Wai
🔗
|
-
|
Query Design for Crowdsourced Clustering: Effect of Cognitive Overload and Contextual Bias
(
Poster
)
>
link
|
Yi Chen · Ramya Vinayak
🔗
|
-
|
An Electoral Approach to Diversify LLM-based Multi-Agent Collective Decision-Making
(
Poster
)
>
link
|
Xiutian Zhao · Ke Wang · Wei Peng
🔗
|
-
|
Do LLM Agents Have Regret? A Case Study in Online Learning and Games
(
Poster
)
>
link
|
Chanwoo Park · Xiangyu Liu · Asuman Ozdaglar · Kaiqing Zhang
🔗
|
-
|
Multi-Agent Imitation Learning: Value is Easy, Regret is Hard
(
Poster
)
>
link
|
Jingwu Tang · Gokul Swamy · Fei Fang · Steven Wu
🔗
|
-
|
Towards Safe Large Language Models for Medicine
(
Poster
)
>
link
|
Tessa Han · Aounon Kumar · Chirag Agarwal · Himabindu Lakkaraju
🔗
|
-
|
Generative AI Misuse: A Taxonomy of Tactics and Insights from Media Data
(
Poster
)
>
link
|
Nahema Marchal · Rachel Xu · Rasmi Elasmar · Iason Gabriel · Beth Goldberg · William Isaac
🔗
|
-
|
Fair Allocation in Dynamic Mechanism Design
(
Poster
)
>
link
|
Alireza Fallah · Michael Jordan · Annie Ulichney
🔗
|
-
|
AIs Favoring AIs: Large Language Models Favor Their Own Generated Content
(
Poster
)
>
link
|
Walter Laurito · Benjamin Davis · peli grietzer · Tomáš Gavenčiak · Ada Böhm · Jan Kulveit
🔗
|