1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.MA2024
Improving Global Parameter-sharing in Physically Heterogeneous Multi-agent Reinforcement Learning with Unified Action Space
Xiaoyang Yu, Youfang Lin, Shuo Wang +2
In a multi-agent system (MAS), action semantics indicates the different influences of agents' actions toward other entities, and can be used to divide agents into groups in a physi…
cs.CL2024★ 1 cited
Say More with Less: Understanding Prompt Learning Behaviors through Gist Compression
Xinze Li, Zhenghao Liu, Chenyan Xiong +4
Large language models (LLMs) require lengthy prompts as the input context to produce output aligned with user intentions, a process that incurs extra costs during inference. In thi…