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
Paper • 2410.23743 • Published • 63 -
Direct Preference Optimization Using Sparse Feature-Level Constraints
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Transformer^2: Self-adaptive LLMs
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Control LLM: Controlled Evolution for Intelligence Retention in LLM
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Taming LLMs by Scaling Learning Rates with Gradient Grouping
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Leveraging Self-Attention for Input-Dependent Soft Prompting in LLMs
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All is Not Lost: LLM Recovery without Checkpoints
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SRFT: A Single-Stage Method with Supervised and Reinforcement Fine-Tuning for Reasoning
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Optimizing ML Training with Metagradient Descent
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Towards a Unified View of Large Language Model Post-Training
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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
Paper • 2510.18866 • Published • 106