Timage generates text query overlays on images via Constrained Schrödinger Bridge to boost fine-grained spatial reasoning in vision-language models, outperforming larger systems on VMCBench with a 7B backbone.
Visual prompt tuning for test-time domain adaptation.arXiv preprint arXiv:2210.04831
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IMSE adapts Vision Transformers for test-time and continual test-time adaptation by tuning only singular values from SVD decompositions and using expert diversity plus domain retrieval, reaching SOTA with far fewer trainable parameters.
SS-TPT uses stability and suitability scores on augmented views to guide test-time prompt tuning and weighted prediction for improved adversarial robustness in VLMs with better robustness-throughput balance.
citing papers explorer
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Timage: A Generative Text-in-Image Paradigm for Fine-Tuning Vision-Language Models
Timage generates text query overlays on images via Constrained Schrödinger Bridge to boost fine-grained spatial reasoning in vision-language models, outperforming larger systems on VMCBench with a 7B backbone.
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IMSE: Intrinsic Mixture of Spectral Experts Fine-tuning for Test-Time Adaptation
IMSE adapts Vision Transformers for test-time and continual test-time adaptation by tuning only singular values from SVD decompositions and using expert diversity plus domain retrieval, reaching SOTA with far fewer trainable parameters.
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SS-TPT: Stability and Suitability-Guided Test-Time Prompt Tuning for Adversarially Robust Vision-Language Models
SS-TPT uses stability and suitability scores on augmented views to guide test-time prompt tuning and weighted prediction for improved adversarial robustness in VLMs with better robustness-throughput balance.