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cs.LG2026
Preference-Based Self-Distillation: Beyond KL Matching via Reward Regularization
Xin Yu, Liuchen Liao, Yiwen Zhang +3
On-policy distillation is an efficient alternative to reinforcement learning, offering dense token-level training signals. However, its reliance on a stronger external teacher has…
cs.LG2025★ 1 cited
Train Large, Deploy Compact: Structured Compression for Compact Low-Rank Adaptation
Xin Yu, Cong Xie, Xunmei Liu +3
Low-rank adaptation (LoRA) has become a widely used paradigm for parameter-efficient fine-tuning of large language models, yet its representational capacity often lags behind full…
cs.LG2025
AltLoRA: Towards Better Gradient Approximation in Low-Rank Adaptation with Alternating Projections
Xin Yu, Yujia Wang, Jinghui Chen +1
Low-Rank Adaptation (LoRA) has emerged as an effective technique for reducing memory overhead in fine-tuning large language models. However, it often suffers from sub-optimal perfo…