VIT-Pro: Visual Instruction Tuning for Product Images
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Vishnu Prabhakaran, Purav Aggarwal, Vishruit Kulshreshtha, Arunita Das, Sahini Venkata Sitaram Sruti, Anoop Saladi. Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 3: Industry Track). 2025.
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Recent research suggests that VLMs require fine-tuning for good performance in recognizing products and their attributes.
“For recognizing products and their attributes, recent research suggests that VLMs require fi ne-tuning for good performance [104, 125].”
From "It's trained by non-disabled people": Evaluating How Image Quality Affects Product Captioning with Vision-Language Models (2026) · cites this paper as [104]
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Cited by
Sorted by citations
Garg, K., Tang, X., Heo, J., Morgan, D. R., Gergle, D., Sudderth, E. B., & Piper, A. M. (2026) · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3791309 · Cited by 3 · see citing works
“For recognizing products and their attributes, recent research suggests that VLMs require fine-tuning for good performance [104, 125].”
- Authors
- Prabhakaran, V., Aggarwal, P., Kulshreshtha, V., Das, A., Sruti, S. V. S., & Saladi, A.
- Affiliations
- Amazon (United States) (US)
- Venue
- Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 3: Industry Track)
- Published
- 2025
- Pages
- 695-707
- OpenAlex
- W4411119644
- Cited by
- 0
- References
- 0
- FWCI
- 0.00
- Type
- conference paper
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by
- Locations
- Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) (publishedVersion, cc-by)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Multimodal Machine Learning Applications
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
- Keywords
- visual instruction tuning, product image, image captioning, instruction tuning
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