37 citations · 64 across the 6 of their papers we have counts for
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cs.LG2026
EMA Policy Gradient: Taming Reinforcement Learning for LLMs with EMA Anchor and Top-k KL
Lunjun Zhang, Jimmy Ba
Reinforcement Learning (RL) has enabled Large Language Models (LLMs) to acquire increasingly complex reasoning and agentic behaviors. In this work, we propose two simple techniques…
cs.LG2024★ 13 cited
The WMDP Benchmark: Measuring and Reducing Malicious Use With Unlearning
Nathaniel Li, Alexander Pan, Anjali Gopal +54
The White House Executive Order on Artificial Intelligence highlights the risks of large language models (LLMs) empowering malicious actors in developing biological, cyber, and che…
cs.LG2023★ 7 cited
Using Large Language Models for Hyperparameter Optimization
Michael R. Zhang, Nishkrit Desai, Juhan Bae +2
This paper explores the use of foundational large language models (LLMs) in hyperparameter optimization (HPO). Hyperparameters are critical in determining the effectiveness of mach…