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cs.MA2024
Towards Efficient Collaboration via Graph Modeling in Reinforcement Learning
Wenzhe Fan, Zishun Yu, Chengdong Ma +3
In multi-agent reinforcement learning, a commonly considered paradigm is centralized training with decentralized execution. However, in this framework, decentralized execution rest…
cs.CL2024★ 2 cited
Language Models Resist Alignment: Evidence From Data Compression
Jiaming Ji, Kaile Wang, Tianyi Qiu +7
Large language models (LLMs) may exhibit unintended or undesirable behaviors. Recent works have concentrated on aligning LLMs to mitigate harmful outputs. Despite these efforts, so…