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cs.CL2025
TL;DR: Too Long, Do Re-weighting for Efficient LLM Reasoning Compression
Zhong-Zhi Li, Xiao Liang, Zihao Tang +11
Large Language Models (LLMs) have recently achieved remarkable progress by leveraging Reinforcement Learning and extended Chain-of-Thought (CoT) techniques. However, the challenge…
cs.CL2025
Infinite-Instruct: Synthesizing Scaling Code instruction Data with Bidirectional Synthesis and Static Verification
Wenjing Xing, Wenke Lu, Yeheng Duan +5
Traditional code instruction data synthesis methods suffer from limited diversity and poor logic. We introduce Infinite-Instruct, an automated framework for synthesizing high-quali…
cs.CL2024
Enhancing the Reasoning Capabilities of Small Language Models via Solution Guidance Fine-Tuning
Jing Bi, Yuting Wu, Weiwei Xing +1
Large language models (LLMs) have demonstrated remarkable performance across a wide range of tasks. Advances in prompt engineering and fine-tuning techniques have further enhanced…