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cs.CL2026
HumanLLM: Benchmarking and Improving LLM Anthropomorphism via Human Cognitive Patterns
Xintao Wang, Jian Yang, Weiyuan Li +8
Large Language Models (LLMs) have demonstrated remarkable capabilities in reasoning and generation, serving as the foundation for advanced persona simulation and Role-Playing Langu…
cs.CL2024
C3oT: Generating Shorter Chain-of-Thought without Compromising Effectiveness
Yu Kang, Xianghui Sun, Liangyu Chen +1
Generating Chain-of-Thought (CoT) before deriving the answer can effectively improve the reasoning capabilities of large language models (LLMs) and significantly improve the accura…
cs.CL2024
Improving embedding with contrastive fine-tuning on small datasets with expert-augmented scores
Jun Lu, David Li, Bill Ding +1
This paper presents an approach to improve text embedding models through contrastive fine-tuning on small datasets augmented with expert scores. It focuses on enhancing semantic te…