Author

Siru Jiang

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#machine learning Preprint Sep 2026

To Adapt or Not to Adapt? Selective Adaptation for Vision-Language Models

Test-time adaptation (TTA) has emerged as a prominent strategy for adapting vision-language models to distribution shifts during inference. We conduct a per-sample analysis of model predictions before and after adaptation, and observe two failure modes in existing TTA methods that echo previous work. Adaptations are fr...

Si-Ru Jiang, Yu-Wei Liang, Jian Liang et al. · 1 citation

Preprint Jul 2026

USE: A Unified Self-Ensembling Framework for Test-Time Prompt Tuning

Test-time adaptation (TTA) has emerged as a popular paradigm for improving the performance of vision-language models (e.g., CLIP) on downstream tasks. Among existing CLIP-based TTA methods, Test-Time Prompt Tuning (TPT) is a pioneering work that optimizes textual prompts using multiple test-time augmentations and remai...

Siru Jiang, Jian Liang, Ran He et al. · 0 citations