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cs.CL2026
Understanding Knowledge Distillation in Post-Training: When It Helps and When It Fails
Xin Liu, Simin Ma, Shujian Liu +5
Large language models (LLMs) achieve strong performance across many tasks, but their high computational cost limits deployment in resource-constrained environments. Knowledge Disti…
cs.CL2025
Aligning Multilingual Reasoning with Verifiable Semantics from a High-Resource Expert Model
Fahim Faisal, Kaiqiang Song, Song Wang +4
While reinforcement learning has advanced the reasoning abilities of Large Language Models (LLMs), these gains are largely confined to English, creating a significant performance d…