7 papers
SemEval-2026 Task 12: Abductive Event Reasoning: Towards Real-World Event Causal Inference for Large Language Models
Pengfei Cao, Mingxuan Yang, Yubo Chen +4
Understanding why real-world events occur is important for both natural language processing and practical decision-making, yet direct-cause inference remains underexplored in evide…
GIP-RAG: An Evidence-Grounded Retrieval-Augmented Framework for Interpretable Gene Interaction and Pathway Impact Analysis
Fujian Jia, Jiwen Gu, Cheng Lu +5
Understanding mechanistic relationships among genes and their impacts on biological pathways is essential for elucidating disease mechanisms and advancing precision medicine. Despi…
Towards Agentic Self-Learning LLMs in Search Environment
Wangtao Sun, Xiang Cheng, Jialin Fan +5
We study whether self-learning can scale LLM-based agents without relying on human-curated datasets or predefined rule-based rewards. Through controlled experiments in a search-age…
Amplify Adjacent Token Differences: Enhancing Long Chain-of-Thought Reasoning with Shift-FFN
Yao Xu, Mingyu Xu, Fangyu Lei +7
Recently, models such as OpenAI-o1 and DeepSeek-R1 have demonstrated remarkable performance on complex reasoning tasks through Long Chain-of-Thought (Long-CoT) reasoning. Although…
Probabilistic Uncertain Reward Model
Wangtao Sun, Xiang Cheng, Xing Yu +5
Reinforcement learning from human feedback (RLHF) is a critical technique for training large language models. However, conventional reward models based on the Bradley-Terry model (…
Shuttle Between the Instructions and the Parameters of Large Language Models
Wangtao Sun, Haotian Xu, Huanxuan Liao +5
The interaction with Large Language Models (LLMs) through instructions has been extensively investigated in the research community. While instructions have been widely used as the…