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cs.AI2026
Leave it to the Specialist: Repair Sparse LLMs with Sparse Fine-Tuning via Sparsity Evolution
Qiao Xiao, Alan Ansell, Boqian Wu +4
Sparse large language models (LLMs) offer an attractive direction toward efficient deployment, but adapting them to downstream tasks remains challenging. The central difficulty is…
cs.AI2026
Demystifying the Roles of LLM Layers in Retrieval, Knowledge, and Reasoning
Xinyuan Song, Keyu Wang, PengXiang Li +2
Recent studies suggest that the deeper layers of Large Language Models (LLMs) contribute little to representation learning and can often be removed without significant performance…
cs.AI2025
Effective Learning for Small Reasoning Models: An Empirical Study on 0.5B Reasoning LLMs
Xialie Zhuang, Peixian Ma, Zhikai Jia +2
The ongoing evolution of language models has led to the development of large-scale architectures that demonstrate exceptional performance across a wide range of tasks. However, the…