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cs.LG2026
A Unified Study of LoRA Variants: Taxonomy, Review, Codebase, and Empirical Evaluation
Haonan He, Jingqi Ye, Minglei Li +4
Low-Rank Adaptation (LoRA) is a fundamental parameter-efficient fine-tuning method that balances efficiency and performance in large-scale neural networks. However, the proliferati…
cs.LG2025
P1: Mastering Physics Olympiads with Reinforcement Learning
Jiacheng Chen, Qianjia Cheng, Fangchen Yu +25
Recent progress in large language models (LLMs) has moved the frontier from puzzle-solving to science-grade reasoning-the kind needed to tackle problems whose answers must stand ag…
cs.LG2025
GoRA: Gradient-driven Adaptive Low Rank Adaptation
Haonan He, Peng Ye, Yuchen Ren +4
Low-Rank Adaptation (LoRA) is a crucial method for efficiently fine-tuning large language models (LLMs), with its effectiveness influenced by two key factors: rank selection and we…