Author

Run-Min Wang

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Preprint Aug 2026

GATE: Reliability-Gated Gaussian Evidence Fusion for Training-Free Test-Time Adaptation of Vision-Language Models

GATE is introduced, a training-free two-pass transductive test-time adaptation framework that uses the unlabeled target set while keeping the image encoder, text encoder, and prompt parameters fully frozen, and demonstrates the benefit of reliability-gated distributional evidence for frozen VLM adaptation.

Pedram MohajerAnsari, Amir Salarpour, Run-Min Wang et al. · 0 citations

Jul 2026

Adversarial Prompts for Acceptance Collapse in Speculative Decoding

ADSD is introduced, which is the first prompt-suffix attack that collapses verifier acceptance by pushing draft probability mass toward tokens the target is unlikely to accept, and successfully generates highly effective adversarial suffixes.

Run-Min Wang, Chaoyi Zhou, Xi Liu et al. · arXiv.org · 0 citations