Papers
Predicting and Interpreting Energy Barriers of Metallic Glasses with Graph Neural Networks
Haoyu Li, Shichang Zhang, Longwen Tang et al.
Predicting Dose-Response Curves with Deep Neural Networks
Pedro Alonso Campana, Paul Prasse, Tobias Scheffer
Predicting Lagrangian Multipliers for Mixed Integer Linear Programs
Francesco Demelas, Joseph Le Roux, Mathieu Lacroix et al.
Prediction Accuracy of Learning in Games : Follow-the-Regularized-Leader meets Heisenberg
Yi Feng, Georgios Piliouras, Xiao Wang
Prediction-powered Generalization of Causal Inferences
Ilker Demirel, Ahmed Alaa, Anthony Philippakis et al.
Predictive Coding beyond Correlations
Tommaso Salvatori, Luca Pinchetti, Amine M’Charrak et al.
Predictive Dynamic Fusion
Bing Cao, Yinan Xia, Yi Ding et al.
Predictive Linear Online Tracking for Unknown Targets
Anastasios Tsiamis, Aren Karapetyan, Yueshan Li et al.
Predictive Performance Comparison of Decision Policies Under Confounding
Luke Guerdan, Amanda Lee Coston, Ken Holstein et al.
Preference Fine-Tuning of LLMs Should Leverage Suboptimal, On-Policy Data
Fahim Tajwar, Anikait Singh, Archit Sharma et al.
Preference Optimization for Molecule Synthesis with Conditional Residual Energy-based Models
Songtao Liu, Hanjun Dai, Yue Zhao et al.
Premier-TACO is a Few-Shot Policy Learner: Pretraining Multitask Representation via Temporal Action-Driven Contrastive Loss
Ruijie Zheng, Yongyuan Liang, Xiyao Wang et al.
Premise Order Matters in Reasoning with Large Language Models
Xinyun Chen, Ryan Andrew Chi, Xuezhi Wang et al.
PrE-Text: Training Language Models on Private Federated Data in the Age of LLMs
Charlie Hou, Akshat Shrivastava, Hongyuan Zhan et al.
Pre-Training Protein Bi-level Representation Through Span Mask Strategy On 3D Protein Chains
Zhao Jiale, Wanru Zhuang, Jia Song et al.
Preventing Model Collapse in Gaussian Process Latent Variable Models
Ying Li, Zhidi Lin, Feng Yin et al.
Pricing with Contextual Elasticity and Heteroscedastic Valuation
Jianyu Xu, Yu-Xiang Wang
Principled Gradient-Based MCMC for Conditional Sampling of Text
Li Du, Afra Amini, Lucas Torroba Hennigen et al.
Principled Penalty-based Methods for Bilevel Reinforcement Learning and RLHF
Han Shen, Zhuoran Yang, Tianyi Chen
Principled Preferential Bayesian Optimization
Wenjie Xu, Wenbin Wang, Yuning Jiang et al.
PriorBoost: An Adaptive Algorithm for Learning from Aggregate Responses
Adel Javanmard, Matthew Fahrbach, Vahab Mirrokni
Prior Mismatch and Adaptation in PnP-ADMM with a Nonconvex Convergence Analysis
Shirin Shoushtari, Jiaming Liu, Edward P. Chandler et al.
PRISE: LLM-Style Sequence Compression for Learning Temporal Action Abstractions in Control
Ruijie Zheng, Ching-An Cheng, Hal Daumé Iii et al.
Prismatic VLMs: Investigating the Design Space of Visually-Conditioned Language Models
Siddharth Karamcheti, Suraj Nair, Ashwin Balakrishna et al.
Privacy Attacks in Decentralized Learning
Abdellah El Mrini, Edwige Cyffers, Aurélien Bellet