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TTRSD: Test-Time Reinforcement Learning with Self-Distillation for Vision-Language Models
Test-time reinforcement learning enables vision-language models (VLMs) to adapt using unlabeled inputs. However, repeated sampling under fixed visual conditions can reinforce shared perceptual errors, while sequence-level rewards fail to isolate visual perception the foundational bottleneck that anc
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