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ReNFT: Repairing Mode Collapse in Reward Post-Training via Internal Probability-Mass Recalibration
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mode collapsereward post-trainingdiversity enhancementprobability recalibration
2609.00061
Builder Relevance
1h ago80%
Abstract
ReNFT addresses mode collapse in reward post-training of diffusion generators by recalibrating internal probability mass to restore diversity without losing acquired rewards.
Reality Card
Core Claim
ReNFT successfully repairs a high-reward, low-diversity adapter, improving diversity metrics while retaining nearly all of the original reward.
Method / Result
ReNFT improves DreamSim-Div by 58.8% and 55.0% on PickScore and GenEval, respectively.
Limitations
The paper does not specify authors or detailed experimental setups, which may hinder reproducibility.
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