8 papers
MeasHalu: Mitigation of Scientific Measurement Hallucinations for Large Language Models with Enhanced Reasoning
Ruijun Huang, Zhiqiao Kang, Yuxuan Zhu +5
The accurate extraction of scientific measurements from literature is a critical yet challenging task in AI4Science, enabling large-scale analysis and integration of quantitative r…
PLOT: Enhancing Preference Learning via Optimal Transport
Liang Zhu, Yuelin Bai, Xiankun Ren +6
Preference learning in Large Language Models (LLMs) has advanced significantly, yet existing methods remain limited by modest performance gains, high computational costs, hyperpara…
DEFT: Distribution-guided Efficient Fine-Tuning for Human Alignment
Liang Zhu, Feiteng Fang, Yuelin Bai +4
Reinforcement Learning from Human Feedback (RLHF), using algorithms like Proximal Policy Optimization (PPO), aligns Large Language Models (LLMs) with human values but is costly and…
Structuring Reasoning for Complex Rules Beyond Flat Representations
Zhihao Yang, Ancheng Xu, Jingpeng Li +11
Large language models (LLMs) face significant challenges when processing complex rule systems, as they typically treat interdependent rules as unstructured textual data rather than…
LongEmotion: Measuring Emotional Intelligence of Large Language Models in Long-Context Interaction
Weichu Liu, Jing Xiong, Yuxuan Hu +10
Large language models (LLMs) have made significant progress in Emotional Intelligence (EI) and long-context modeling. However, existing benchmarks often overlook the fact that emot…
RxSafeBench: Identifying Medication Safety Issues of Large Language Models in Simulated Consultation
Jiahao Zhao, Luxin Xu, Minghuan Tan +4
Numerous medical systems powered by Large Language Models (LLMs) have achieved remarkable progress in diverse healthcare tasks. However, research on their medication safety remains…