A unified theory for RE(S) is developed that covers the full spectrum of S, and can be interpreted as a stage-wise optimization process, where each stage takes $S$ gradient steps for minimizing the Kullback-Leibler distance to a fixed reward-weighted rollout distribution.
Zhi-Wei Wang, Yan-Xi Chen, Ya-Liang Li et al.· 0 citations
This paper formalizes preference privacy, a label-DP-style privacy notion for DPO that protects only the relative preference between candidate responses, assuming an adversary who already knows the prompt and responses, and designs PrivDPO, a DPO variant that enforces preference privacy while remaining compatible with...
Yang-Fan Jiang, Fei Wei, Ergute Bao et al.· 0 citations
LLM agents increasingly take on long-running tasks whose history grows far beyond a single model context window. Existing approaches compress earlier interactions or extract selected information into fixed memory representations, committing to what to preserve before future needs are known. We present Scroll, a context...
EvoSOP is introduced, a framework that empowers agents to extract SOPs from execution trajectories and iteratively optimize the toolset through a systematic lifecycle of construction, merging, evaluation, and pruning, providing a scalable pathway for the development of self-evolving agents.
Haipeng Ding, Yuexiang Xie, Zhewei Wei et al.· 2 citations
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