Papers
Learning to Discover Regulatory Elements for Gene Expression Prediction
Xingyu Su, Haiyang Yu, Degui Zhi et al.
Rapidly Adapting Policies to the Real-World via Simulation-Guided Fine-Tuning
Patrick Yin, Tyler Westenbroek, Ching-An Cheng et al.
What Matters in Learning from Large-Scale Datasets for Robot Manipulation
Vaibhav Saxena, Matthew Bronars, Nadun Ranawaka Arachchige et al.
Global Convergence of Policy Gradient in Average Reward MDPs
Navdeep Kumar, Yashaswini Murthy, Itai Shufaro et al.
Human-inspired Episodic Memory for Infinite Context LLMs
Zafeirios Fountas, Martin Benfeghoul, Adnan Oomerjee et al.
Lossy Compression with Pretrained Diffusion Models
Jeremy Vonderfecht, Feng Liu
Estimating the Probabilities of Rare Outputs in Language Models
Gabriel Wu, Jacob Hilton
ClimaQA: An Automated Evaluation Framework for Climate Question Answering Models
Veeramakali Vignesh Manivannan, Yasaman Jafari, Srikar Eranky et al.
Benign Overfitting in Out-of-Distribution Generalization of Linear Models
Shange Tang, Jiayun Wu, Jianqing Fan et al.
Locality Alignment Improves Vision-Language Models
Ian Connick Covert, Tony Sun, James Zou et al.
L3Ms — Lagrange Large Language Models
Guneet S. Dhillon, Xingjian Shi, Yee Whye Teh et al.
Risk-Sensitive Variational Actor-Critic: A Model-Based Approach
Alonso Granados, Reza Ebrahimi, Jason Pacheco
ORSO: Accelerating Reward Design via Online Reward Selection and Policy Optimization
Chen Bo Calvin Zhang, Zhang-Wei Hong, Aldo Pacchiano et al.
No Need to Talk: Asynchronous Mixture of Language Models
Anastasiia Filippova, Angelos Katharopoulos, David Grangier et al.
Beyond-Expert Performance with Limited Demonstrations: Efficient Imitation Learning with Double Exploration
Heyang Zhao, Xingrui Yu, David Mark Bossens et al.
Value-Incentivized Preference Optimization: A Unified Approach to Online and Offline RLHF
Shicong Cen, Jincheng Mei, Katayoon Goshvadi et al.
AgentOccam: A Simple Yet Strong Baseline for LLM-Based Web Agents
Ke Yang, Yao Liu, Sapana Chaudhary et al.
MaestroMotif: Skill Design from Artificial Intelligence Feedback
Martin Klissarov, Mikael Henaff, Roberta Raileanu et al.
Probe Pruning: Accelerating LLMs through Dynamic Pruning via Model-Probing
Qi Le, Enmao Diao, Ziyan Wang et al.
Humanizing the Machine: Proxy Attacks to Mislead LLM Detectors
Tianchun Wang, Yuanzhou Chen, Zichuan Liu et al.
Learning-Guided Rolling Horizon Optimization for Long-Horizon Flexible Job-Shop Scheduling
Sirui Li, Wenbin Ouyang, Yining Ma et al.
ImProver: Agent-Based Automated Proof Optimization
Riyaz Ahuja, Jeremy Avigad, Prasad Tetali et al.
Token-Supervised Value Models for Enhancing Mathematical Problem-Solving Capabilities of Large Language Models
Jung Hyun Lee, June Yong Yang, Byeongho Heo et al.
Reward Learning from Multiple Feedback Types
Yannick Metz, Andras Geiszl, Raphaël Baur et al.
Directional Gradient Projection for Robust Fine-Tuning of Foundation Models
Chengyue Huang, Junjiao Tian, Brisa Maneechotesuwan et al.