When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method
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2402.17193
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Published
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26
Fine tuning
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What Happened in LLMs Layers when Trained for Fast vs. Slow Thinking: A Gradient Perspective
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Direct Preference Optimization Using Sparse Feature-Level Constraints
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Optimizing ML Training with Metagradient Descent
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Analyzing the Effects of Supervised Fine-Tuning on Model Knowledge from Token and Parameter Levels
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Fine-tuning Done Right in Model Editing
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Interactive Training: Feedback-Driven Neural Network Optimization
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LightMem: Lightweight and Efficient Memory-Augmented Generation
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π_RL: Online RL Fine-tuning for Flow-based Vision-Language-Action Models
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ROOT: Robust Orthogonalized Optimizer for Neural Network Training
Paper • 2511.20626 • Published • 43 -
Good SFT Optimizes for SFT, Better SFT Prepares for Reinforcement Learning
Paper • 2602.01058 • Published • 39 -
MSign: An Optimizer Preventing Training Instability in Large Language Models via Stable Rank Restoration
Paper • 2602.01734 • Published • 31