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How Well do LLMs Compress Their Own Chain-of-Thought? A Token Complexity Approach
Ayeong Lee, Ethan Che, Tianyi Peng
Chain-of-thought prompting has emerged as a powerful technique for enabling large language models (LLMs) to solve complex reasoning tasks. However, these reasoning chains can be ve…
cs.CL2025
LLM Generated Persona is a Promise with a Catch
Ang Li, Haozhe Chen, Hongseok Namkoong +1
The use of large language models (LLMs) to simulate human behavior has gained significant attention, particularly through personas that approximate individual characteristics. Pers…