most citedConfronting Reward Model Overoptimization with Constrained RLHF

1 citations · 1 across the 2 of their papers we have counts for

collaborators

6 papers

cs.AI2024

Grasper: A Generalist Pursuer for Pursuit-Evasion Problems

Pengdeng Li, Shuxin Li, Xinrun Wang +5

Pursuit-evasion games (PEGs) model interactions between a team of pursuers and an evader in graph-based environments such as urban street networks. Recent advancements have demonst…

cs.GT2024

Faster Game Solving via Hyperparameter Schedules

Naifeng Zhang, Stephen McAleer, Tuomas Sandholm

Counterfactual regret minimization (CFR) algorithms are a foundational class of methods for solving imperfect-information games, with the time average of their iterates converging…

cs.GT2024

Automated Design of Affine Maximizer Mechanisms in Dynamic Settings

Michael Curry, Vinzenz Thoma, Darshan Chakrabarti +5

Dynamic mechanism design is a challenging extension to ordinary mechanism design in which the mechanism designer must make a sequence of decisions over time in the face of possibly…

cs.AI2024

Scalable Mechanism Design for Multi-Agent Path Finding

Paul Friedrich, Yulun Zhang, Michael Curry +5

Multi-Agent Path Finding (MAPF) involves determining paths for multiple agents to travel simultaneously and collision-free through a shared area toward given goal locations. This p…

cs.LG20231 cited

Confronting Reward Model Overoptimization with Constrained RLHF

Ted Moskovitz, Aaditya K. Singh, DJ Strouse +4

Large language models are typically aligned with human preferences by optimizing (RMs) fitted to human feedback. However, human preferences are multi-facet…

cs.CL2023

Llemma: An Open Language Model For Mathematics

Zhangir Azerbayev, Hailey Schoelkopf, Keiran Paster +6

We present Llemma, a large language model for mathematics. We continue pretraining Code Llama on the Proof-Pile-2, a mixture of scientific papers, web data containing mathematics,…