3 papers
cs.LG2026
DynamicPTQ: Mitigating Activation Quantization Collapse via Residual-Stream Dynamics
Zimo Zhao, Maolin Wang, Bowen Yu +3
Post-training quantization (PTQ) is essential for efficient large language model inference, but reliably quantizing activations remains challenging when weights, activations, and K…
cs.LG2026
BRIDGE: Bridging Reasoning In Distillation Gap Elimination via Structure-Aware Masking
Bowen Yu, Sheng Zhang, Binhao Wang +8
Chain-of-Thought (CoT) reasoning has significantly improved LLMs' mathematical problem-solving capabilities, but distilling such capabilities into smaller models remains challengin…
cs.AI2025
Data Efficient Adaptation in Large Language Models via Continuous Low-Rank Fine-Tuning
Xiao Han, Zimo Zhao, Wanyu Wang +4
Recent advancements in Large Language Models (LLMs) have emphasized the critical role of fine-tuning (FT) techniques in adapting LLMs to specific tasks, especially when retraining…