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cs.LG2025
KDRL: Post-Training Reasoning LLMs via Unified Knowledge Distillation and Reinforcement Learning
Hongling Xu, Qi Zhu, Heyuan Deng +6
Recent advances in large language model (LLM) post-training have leveraged two distinct paradigms to enhance reasoning capabilities: reinforcement learning (RL) and knowledge disti…
cs.LG2024★ 2 cited
OAC: Output-adaptive Calibration for Accurate Post-training Quantization
Ali Edalati, Alireza Ghaffari, Mahsa Ghazvini Nejad +4
Deployment of Large Language Models (LLMs) has major computational costs, due to their rapidly expanding size. Compression of LLMs reduces the memory footprint, latency, and energy…