3 papers
cs.CL2026
ActiShade: Activating Overshadowed Knowledge to Guide Multi-Hop Reasoning in Large Language Models
Huipeng Ma, Luan Zhang, Dandan Song +10
In multi-hop reasoning, multi-round retrieval-augmented generation (RAG) methods typically rely on LLM-generated content as the retrieval query. However, these approaches are inher…
cs.AI2025
SCoder: Iterative Self-Distillation for Bootstrapping Small-Scale Data Synthesizers to Empower Code LLMs
Xinyu Zhang, Changzhi Zhou, Linmei Hu +5
Existing code large language models (LLMs) often rely on large-scale instruction data distilled from proprietary LLMs for fine-tuning, which typically incurs high costs. In this pa…
cs.CL2025
RefineCoder: Iterative Improving of Large Language Models via Adaptive Critique Refinement for Code Generation
Changzhi Zhou, Xinyu Zhang, Dandan Song +6
Code generation has attracted increasing attention with the rise of Large Language Models (LLMs). Many studies have developed powerful code LLMs by synthesizing code-related instru…