Papers
Position: Theory of Mind Benchmarks are Broken for Large Language Models
Matthew Riemer, Zahra Ashktorab, Djallel Bouneffouf et al.
Position: An Empirically Grounded Identifiability Theory Will Accelerate Self Supervised Learning Research
Patrik Reizinger, Randall Balestriero, David Klindt et al.
Position: AI’s growing due process problem
Sunayana Rane
Position: Principles of Animal Cognition to Improve LLM Evaluations
Sunayana Rane, Cyrus F. Kirkman, Graham Todd et al.
Position: All Current Generative Fidelity and Diversity Metrics are Flawed
Ossi Räisä, Boris Van Breugel, Mihaela Van Der Schaar
Position: Causal Machine Learning Requires Rigorous Synthetic Experiments for Broader Adoption
Audrey Poinsot, Panayiotis Panayiotou, Alessandro Leite et al.
Position: Explainable AI Cannot Advance Without Better User Studies
Matej Pičulin, Bernarda Petek, Irena Ograjenšek et al.
Position: Iterative Online-Offline Joint Optimization is Needed to Manage Complex LLM Copyright Risks
Yanzhou Pan, Jiayi Chen, Jiamin Chen et al.
Position: Democratic AI is Possible. The Democracy Levels Framework Shows How It Might Work.
Aviv Ovadya, Kyle Redman, Luke Thorburn et al.
Position: Solve Layerwise Linear Models First to Understand Neural Dynamical Phenomena (Neural Collapse, Emergence, Lazy/Rich Regime, and Grokking)
Yoonsoo Nam, Seok Hyeong Lee, Clémentine Carla Juliette Dominé et al.
Position: The Right to AI
Rashid Mushkani, Hugo Berard, Allison Cohen et al.
Position: The Future of Bayesian Prediction Is Prior-Fitted
Samuel Müller, Arik Reuter, Noah Hollmann et al.
Position: Rethinking LLM Bias Probing Using Lessons from the Social Sciences
Kirsten Morehouse, Siddharth Swaroop, Weiwei Pan
Position: Probabilistic Modelling is Sufficient for Causal Inference
Bruno Kacper Mlodozeniec, David Krueger, Richard E Turner
Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives
Elliot Meyerson, Xin Qiu
Position: Lifetime tuning is incompatible with continual reinforcement learning
Golnaz Mesbahi, Parham Mohammad Panahi, Olya Mastikhina et al.
Position: Machine Learning Models Have a Supply Chain Problem
Sarah Meiklejohn, Hayden Blauzvern, Mihai Maruseac et al.
Position: Algebra Unveils Deep Learning - An Invitation to Neuroalgebraic Geometry
Giovanni Luca Marchetti, Vahid Shahverdi, Stefano Mereta et al.
Position: In-House Evaluation Is Not Enough. Towards Robust Third-Party Evaluation and Flaw Disclosure for General-Purpose AI
Shayne Longpre, Kevin Klyman, Ruth Elisabeth Appel et al.
Position: Truly Self-Improving Agents Require Intrinsic Metacognitive Learning
Tennison Liu, Mihaela Van Der Schaar
Position: Supervised Classifiers Answer the Wrong Questions for OOD Detection
Yucen Lily Li, Daohan Lu, Polina Kirichenko et al.
Position: Humanity Faces Existential Risk from Gradual Disempowerment
Jan Kulveit, Raymond Douglas, Nora Ammann et al.
Position: Uncertainty Quantification Needs Reassessment for Large Language Model Agents
Michael Kirchhof, Gjergji Kasneci, Enkelejda Kasneci
Position: You Can’t Manufacture a NeRF
Ma Kimmel, Mueed Ur Rehman, Yonatan Bisk et al.
Position: The AI Conference Peer Review Crisis Demands Author Feedback and Reviewer Rewards
Jaeho Kim, Yunseok Lee, Seulki Lee