3 citations · 3 across the 8 of their papers we have counts for
8 papers
Fast-Slow Thinking RM: Efficient Integration of Scalar and Generative Reward Models
Jiayun Wu, Peixu Hou, Shan Qu +4
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…
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…
MoHoBench: Assessing Honesty of Multimodal Large Language Models via Unanswerable Visual Questions
Yanxu Zhu, Shitong Duan, Xiangxu Zhang +7
Recently Multimodal Large Language Models (MLLMs) have achieved considerable advancements in vision-language tasks, yet produce potentially harmful or untrustworthy content. Despit…
AdAEM: An Adaptively and Automated Extensible Measurement of LLMs' Value Difference
Jing Yao, Shitong Duan, Xiaoyuan Yi +6
Assessing Large Language Models'(LLMs) underlying value differences enables comprehensive comparison of their misalignment, cultural adaptability, and biases. Nevertheless, current…
Value Compass Benchmarks: A Platform for Fundamental and Validated Evaluation of LLMs Values
Jing Yao, Xiaoyuan Yi, Shitong Duan +8
As Large Language Models (LLMs) achieve remarkable breakthroughs, aligning their values with humans has become imperative for their responsible development and customized applicati…
On the Essence and Prospect: An Investigation of Alignment Approaches for Big Models
Xinpeng Wang, Shitong Duan, Xiaoyuan Yi +7
Big models have achieved revolutionary breakthroughs in the field of AI, but they might also pose potential concerns. Addressing such concerns, alignment technologies were introduc…
Negating Negatives: Alignment with Human Negative Samples via Distributional Dispreference Optimization
Shitong Duan, Xiaoyuan Yi, Peng Zhang +5
Large language models (LLMs) have revolutionized the role of AI, yet pose potential social risks. To steer LLMs towards human preference, alignment technologies have been introduce…
Human Still Wins over LLM: An Empirical Study of Active Learning on Domain-Specific Annotation Tasks
Yuxuan Lu, Bingsheng Yao, Shao Zhang +5
Large Language Models (LLMs) have demonstrated considerable advances, and several claims have been made about their exceeding human performance. However, in real-world tasks, domai…