1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2025
Stronger-MAS: Multi-Agent Reinforcement Learning for Collaborative LLMs
Yujie Zhao, Lanxiang Hu, Yang Wang +4
Multi-agent systems (MAS) and reinforcement learning (RL) are widely used to enhance the agentic capabilities of large language models (LLMs). MAS improves task performance through…
cs.CL2024★ 1 cited
HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly
Howard Yen, Tianyu Gao, Minmin Hou +5
Many benchmarks exist for evaluating long-context language models (LCLMs), yet developers often rely on synthetic tasks such as needle-in-a-haystack (NIAH) or an arbitrary subset o…