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cs.CL2025
Code to Think, Think to Code: A Survey on Code-Enhanced Reasoning and Reasoning-Driven Code Intelligence in LLMs
Dayu Yang, Tianyang Liu, Daoan Zhang +8
In large language models (LLMs), code and reasoning reinforce each other: code offers an abstract, modular, and logic-driven structure that supports reasoning, while reasoning tran…
cs.CL2025
Memory-Efficient Fine-Tuning of Transformers via Token Selection
Antoine Simoulin, Namyong Park, Xiaoyi Liu +1
Fine-tuning provides an effective means to specialize pre-trained models for various downstream tasks. However, fine-tuning often incurs high memory overhead, especially for large…