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cs.CL2026
History-Guided Iterative Visual Reasoning with Self-Correction
Xinglong Yang, Zhilin Peng, Zhanzhan Liu +2
Self-consistency methods are the core technique for improving the reasoning reliability of multimodal large language models (MLLMs). By generating multiple reasoning results throug…
cs.CL2025
PHYBench: Holistic Evaluation of Physical Perception and Reasoning in Large Language Models
Shi Qiu, Shaoyang Guo, Zhuo-Yang Song +51
Current benchmarks for evaluating the reasoning capabilities of Large Language Models (LLMs) face significant limitations: task oversimplification, data contamination, and flawed e…
cs.CL2024
Skill-LLM: Repurposing General-Purpose LLMs for Skill Extraction
Amirhossein Herandi, Yitao Li, Zhanlin Liu +2
Accurate skill extraction from job descriptions is crucial in the hiring process but remains challenging. Named Entity Recognition (NER) is a common approach used to address this i…