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cs.CL2025
A Survey on Training-free Alignment of Large Language Models
Birong Pan, Yongqi Li, Weiyu Zhang +6
The alignment of large language models (LLMs) aims to ensure their outputs adhere to human values, ethical standards, and legal norms. Traditional alignment methods often rely on r…
cs.CL2025
Reasoning based on symbolic and parametric knowledge bases: a survey
Mayi Xu, Yunfeng Ning, Yongqi Li +10
Reasoning is fundamental to human intelligence, and critical for problem-solving, decision-making, and critical thinking. Reasoning refers to drawing new conclusions based on exist…
cs.CL2024
Enhancing Relation Extraction via Supervised Rationale Verification and Feedback
Yongqi Li, Xin Miao, Shen Zhou +3
Despite the rapid progress that existing automated feedback methods have made in correcting the output of large language models (LLMs), these methods cannot be well applied to the…