1 citations · 3 across the 8 of their papers we have counts for
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Fast-Slow Thinking RM: Efficient Integration of Scalar and Generative Reward Models
Jiayun Wu, Peixu Hou, Shan Qu +3
Reward models (RMs) are critical for aligning Large Language Models via Reinforcement Learning from Human Feedback (RLHF). While Generative Reward Models (GRMs) achieve superior ac…
IntPro: A Proxy Agent for Context-Aware Intent Understanding via Retrieval-conditioned Inference
Guanming Liu, Meng Wu, Peng Zhang +8
Large language models (LLMs) have become integral to modern Human-AI collaboration workflows, where accurately understanding user intent serves as a crucial step for generating sat…
"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth
Yaqiong Li, Peng Zhang, Lin Wang +4
Risk perception is subjective, and youth's understanding of toxic content differs from that of adults. Although previous research has conducted extensive studies on toxicity detect…
IROTE: Human-like Traits Elicitation of Large Language Model via In-Context Self-Reflective Optimization
Yuzhuo Bai, Shitong Duan, Muhua Huang +7
Trained on various human-authored corpora, Large Language Models (LLMs) have demonstrated a certain capability of reflecting specific human-like traits (e.g., personality or values…