Agents in knowledge-intensive domains require not only knowledge retrieval, but also the skills to effectively use retrieved knowledge. Since domain knowledge is often highly complex, agents must possess strong reasoning capabilities in order to perform tasks effectively. In the legal domain, different legal systems ex...
Yi-Ran Hu, Rong-Xin Cheng, Hai-Tao Li et al.· Proceedings of the 35th ACM...· 0 citations
This work proposes LifeMem, a longitudinal memory framework that combines structured life-event retrieval with agent-specific parametric memory for experience integration, and shows that LifeMem improves alignment with human data in terms of response distributions, overall and within-group diversity, and patterns of wi...
Hexi Wang, Yu-Jia Zhou, Bangde Du et al.· 0 citations
Experimental results across two ranking scenarios demonstrate that explicitly modeling permutation-level differences improves the effectiveness and stability of listwise ranking, with particularly favorable performance in limited-feedback and complex list-level optimization settings.
Yi-Teng Tu, Wei-Hang Su, Zi-Tao Su et al.· arXiv.org· 0 citations
This work introduces LongJudgeBench, a comprehensive benchmark for evaluating LLM judges on long-form outputs across diverse real-world scenarios and judging protocols, and systematically evaluates a broad range of LLM judges, covering multiple base models and judging settings.
Junjie Chen, Yuxin Dong, Haitao Li et al.· arXiv.org· 0 citations
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