Papers
Position: The Categorization of Race in ML is a Flawed Premise
Miriam Doh, Benedikt Höltgen, Piera Riccio et al.
Position: The Future of Bayesian Prediction Is Prior-Fitted
Samuel Müller, Arik Reuter, Noah Hollmann et al.
Position: The Most Expensive Part of an LLM *should* be its Training Data
Nikhil Kandpal, Colin Raffel
Position: Theory of Mind Benchmarks are Broken for Large Language Models
Matthew Riemer, Zahra Ashktorab, Djallel Bouneffouf et al.
Position: The Right to AI
Rashid Mushkani, Hugo Berard, Allison Cohen et al.
Position: Truly Self-Improving Agents Require Intrinsic Metacognitive Learning
Tennison Liu, Mihaela Van Der Schaar
Position: Trustworthy AI Agents Require the Integration of Large Language Models and Formal Methods
Yedi Zhang, Yufan Cai, Xinyue Zuo et al.
Position: Uncertainty Quantification Needs Reassessment for Large Language Model Agents
Michael Kirchhof, Gjergji Kasneci, Enkelejda Kasneci
Position: We Can’t Understand AI Using our Existing Vocabulary
John Hewitt, Robert Geirhos, Been Kim
Position: We Need An Algorithmic Understanding of Generative AI
Oliver Eberle, Thomas Austin Mcgee, Hamza Giaffar et al.
Position: We Need Responsible, Application-Driven (RAD) AI Research
Sarah Hartman, Cheng Soon Ong, Julia Powles et al.
Position: When Incentives Backfire, Data Stops Being Human
Sebastin Santy, Prasanta Bhattacharya, Manoel Horta Ribeiro et al.
Position: You Can’t Manufacture a NeRF
Ma Kimmel, Mueed Ur Rehman, Yonatan Bisk et al.
Positive-unlabeled AUC Maximization under Covariate Shift
Atsutoshi Kumagai, Tomoharu Iwata, Hiroshi Takahashi et al.
Posterior Inference with Diffusion Models for High-dimensional Black-box Optimization
Taeyoung Yun, Kiyoung Om, Jaewoo Lee et al.
Potemkin Understanding in Large Language Models
Marina Mancoridis, Bec Weeks, Keyon Vafa et al.
PPDiff: Diffusing in Hybrid Sequence-Structure Space for Protein-Protein Complex Design
Zhenqiao Song, Tianxiao Li, Lei Li et al.
Preconditioned Riemannian Gradient Descent Algorithm for Low-Multilinear-Rank Tensor Completion
Yuanwei Zhang, Fengmiao Bian, Xiaoqun Zhang et al.
Predicting High-precision Depth on Low-Precision Devices Using 2D Hilbert Curves
Mykhail Uss, Ruslan Yermolenko, Oleksii Shashko et al.
Predicting mutational effects on protein binding from folding energy
Arthur Deng, Karsten D. Householder, Fang Wu et al.
Predicting the Susceptibility of Examples to Catastrophic Forgetting
Guy Hacohen, Tinne Tuytelaars
Prediction-Aware Learning in Multi-Agent Systems
Aymeric Capitaine, Etienne Boursier, Eric Moulines et al.
Prediction models that learn to avoid missing values
Lena Stempfle, Anton Matsson, Newton Mwai et al.
Prediction-Powered Adaptive Shrinkage Estimation
Sida Li, Nikolaos Ignatiadis