2 papers
cs.CL2025
Read Before You Think: Mitigating LLM Comprehension Failures with Step-by-Step Reading
Feijiang Han, Hengtao Cui, Licheng Guo +2
Large Language Models (LLMs) often fail on complex reasoning tasks due to flawed question comprehension, not just flawed logic. This paper presents a systematic investigation into…
cs.CL2024
Training Agents with Weakly Supervised Feedback from Large Language Models
Dihong Gong, Pu Lu, Zelong Wang +2
Large Language Models (LLMs) offer a promising basis for creating agents that can tackle complex tasks through iterative environmental interaction. Existing methods either require…