1 citations · 2 across the 10 of their papers we have counts for
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Calibration, Not Answer Selection: Distilling Internal Confidence in Reasoning Models
Yadong Xi, Rongsheng Zhang, Tangjie Lv +2
Reinforcement learning with binary correctness rewards trains correctness, not calibrated confidence. The confidence that reasoning models verbalize is systematically overconfident…
DynSess: Dynamic Session-Level Evaluation and Optimization Framework for Role-Playing Agents
Rongsheng Zhang, Jiji Tang, Junnan Ren +6
Role-playing with large language models is fundamentally a session-level task, requiring agents to sustain character identity and interaction quality across extended multi-turn con…
From Facts to Insights: A Persona-Driven Dual Memory Framework and Dataset for Role-Playing Agents
Rongsheng Zhang, Ruofan Hu, Weijie Chen +7
While role-playing agents excel in short-term interactions, long-term conversations overwhelm context windows, motivating external memory frameworks. Current systems typically rely…
Ψ-Arena: Interactive Assessment and Optimization of LLM-based Psychological Counselors with Tripartite Feedback
Shijing Zhu, Zhuang Chen, Guanqun Bi +10
Large language models (LLMs) have shown promise in providing scalable mental health support, while evaluating their counseling capability remains crucial to ensure both efficacy an…
Crisp: Cognitive Restructuring of Negative Thoughts through Multi-turn Supportive Dialogues
Jinfeng Zhou, Yuxuan Chen, Jianing Yin +9
Cognitive Restructuring (CR) is a psychotherapeutic process aimed at identifying and restructuring an individual's negative thoughts, arising from mental health challenges, into mo…
CharacterBench: Benchmarking Character Customization of Large Language Models
Jinfeng Zhou, Yongkang Huang, Bosi Wen +13
Character-based dialogue (aka role-playing) enables users to freely customize characters for interaction, which often relies on LLMs, raising the need to evaluate LLMs' character c…
Crafting a Good Prompt or Providing Exemplary Dialogues? A Study of In-Context Learning for Persona-based Dialogue Generation
Jiashu Pu, Yajing Wan, Yuru Zhang +6
Previous in-context learning (ICL) research has focused on tasks such as classification, machine translation, text2table, etc., while studies on whether ICL can improve human-like…