3 papers
cs.CV2026
SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments
Suryanarayana Reddy Yarrabothula, Manisha Chawla, Kunal Sinha +5
Existing video benchmarks evaluate action recognition on consumer videos, egocentric recordings, or simulated industrial environments. They do not test vision-language models under…
cs.LG2025
AdaGradSelect: An adaptive gradient-guided layer selection method for efficient fine-tuning of SLMs
Anshul Kumar, Gagan Raj Gupta, Manisha Chawla
Large Language Models (LLMs) can perform many NLP tasks well, but fully fine-tuning them is expensive and requires a lot of memory. Parameter-Efficient Fine-Tuning (PEFT) methods s…
cs.CV2024
PatchAlign:Fair and Accurate Skin Disease Image Classification by Alignment with Clinical Labels
Aayushman, Hemanth Gaddey, Vidhi Mittal +2
Deep learning models have achieved great success in automating skin lesion diagnosis. However, the ethnic disparity in these models' predictions needs to be addressed before deploy…