一作NeurIPS 2026Poster
Feeling of Knowing in Large Language Models
Zichuan Fu · Xian Wu · Jingtong Gao · Wenlin Zhang · Jiaxuan Li · Binhao Wang · Yimin Deng · Guojing Li · Xiaopeng Li · Derong Xu · Yefeng Zheng · Xiangyu Zhao
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Zichuan Fu · Xian Wu · Jingtong Gao · Wenlin Zhang · Jiaxuan Li · Binhao Wang · Yimin Deng · Guojing Li · Xiaopeng Li · Derong Xu · Yefeng Zheng · Xiangyu Zhao
Yimin Deng · an Jiaotong University) · Zhenxi Lin · Zichuan Fu · Guoshuai Zhao · Derong Xu · Yefeng Zheng · an Jiaotong University) · Xian Wu · Li Zhu · Xueming Qian
Large language models have demonstrated strong reasoning capabilities in general knowledge question answering. However, their ability to handle temporal information remains limited. To address this limitation, existing approaches often design time-sensitive reasoning pipelines that rely on extern...
Yimin Deng · Zhenxi Lin · an Jiaotong University) · Guoshuai Zhao · an Jiaotong University) · Zichuan Fu · Derong Xu · Yefeng Zheng · an Jiaotong University) · Li Zhu · Xian Wu · Xueming Qian
Diagnostic prediction and clinical reasoning are critical tasks in healthcare applications. While large language models have shown strong capabilities in commonsense reasoning, they still struggle with diagnostic reasoning due to limited domain knowledge. Existing approaches often rely on interna...
Zichuan Fu · Xian Wu · Guojing Li · an Jiaotong University) · Yijun Chen · Zhao Zihao · Luo Yixuan · Hanyu Yan · Yefeng Zheng · an Jiaotong University)
Recent advancements in large language models (LLMs) have catalyzed the rise of reasoningintensive inference paradigms, where models perform explicit step-by-step reasoning before generating final answers. While such approaches improve answer quality and interpretability, they incur substantial co...