1 citations · 1 across the 9 of their papers we have counts for
9 papers
HPFA: Hypergraph-Based Paired Failure Attribution for LLM Reasoning
Runchuan Zhu, Hongbin Lai, Bowen Jiang +4
Reflection is a powerful mechanism for LLM reasoning, yet its effectiveness hinges on accurately attributing failures to specific reasoning steps, a capability that current models…
Can Induced Emotion Bias LLM Behaviors in Sequential Decision Making?
Minh Khoi Ho, Zihao Zhu, Runchuan Zhu +4
As Large Language Models (LLMs) are increasingly deployed as autonomous agents in high-stakes domains, understanding contextual factors that may modulate their decision-making beco…
An evidence-guided reinforcement learning method to improve psychiatric reasoning in small language models
Xinxin Lin, Guangxin Dai, Yi Zhong +25
Privacy and computational constraints limit the use of large language models in psychiatry, while adapting small language models (SLMs) often requires substantial data and expert a…
EL4NER: Ensemble Learning for Named Entity Recognition via Multiple Small-Parameter Large Language Models
Yuzhen Xiao, Jiahe Song, Yongxin Xu +6
In-Context Learning (ICL) technique based on Large Language Models (LLMs) has gained prominence in Named Entity Recognition (NER) tasks for its lower computing resource consumption…
Evaluating Large Language Model with Knowledge Oriented Language Specific Simple Question Answering
Bowen Jiang, Runchuan Zhu, Jiang Wu +11
We introduce KoLasSimpleQA, the first benchmark evaluating the multilingual factual ability of Large Language Models (LLMs). Inspired by existing research, we created the question…
3DS: Medical Domain Adaptation of LLMs via Decomposed Difficulty-based Data Selection
Hongxin Ding, Yue Fang, Runchuan Zhu +6
Large Language Models(LLMs) excel in general tasks but struggle in specialized domains like healthcare due to limited domain-specific knowledge.Supervised Fine-Tuning(SFT) data con…