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cs.CL2026
Shuffle the Context: RoPE-Perturbed Self-Distillation for Long-Context Adaptation
Zichong Li, Chen Liang, Liliang Ren +3
Large language models (LLMs) increasingly operate in settings that require reliable long-context understanding, such as retrieval-augmented generation and multi-document reasoning.…
cs.CL2025
LLMs Can Generate a Better Answer by Aggregating Their Own Responses
Zichong Li, Xinyu Feng, Yuheng Cai +6
Large Language Models (LLMs) have shown remarkable capabilities across tasks, yet they often require additional prompting techniques when facing complex problems. While approaches…