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cs.LG2026
Infusion: Shaping Model Behavior by Editing Training Data via Influence Functions
J Rosser, Robert Kirk, Edward Grefenstette +2
Influence functions are commonly used to attribute model behavior to training documents. We explore the reverse: crafting training data that induces model behavior. Our framework,…
cs.LG2025
Generative Data Refinement: Just Ask for Better Data
Minqi Jiang, João G. M. Araújo, Will Ellsworth +2
For a fixed parameter size, the capabilities of large models are primarily determined by the quality and quantity of its training data. Consequently, training datasets now grow fas…