Interactive agents can turn experience into reusable skills, yet existing self-evolving skill libraries primarily improve by accumulating new knowledge. Failures may lead to new skills, while previously stored skills are less often revisited as new evidence arrives. However, growth alone does not ensure reliability, as...
Jie Ma, Zhi-Peng Qian, Yu-Fei Ma et al.· 0 citations
This paper introduces \methodname, the first self-evolving search framework that eliminates difficulty-based proposer rewards and directly optimizes for evidence necessity relative to shortcut contexts, and shows that Dr. Free outperforms prior data-free search agents and the supervised baseline.
Zhi-Peng Qian, Zi-Han Liang, Yu-Fei Ma et al.· 0 citations
This work proposes PRQ-KMeans, which removes the global-mean component, refines centroids with Top-k similarity-weighted updates, and replaces full-codeword subtraction with a projection residual that removes each representation's selected-centroid component.
Yunxiao Luo, Siyuan Wang, Ben Chen et al.· 0 citations
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