3 papers
cs.AI2026
Mechanistically Interpreting Compression in Vision-Language Models
Veeraraju Elluru, Arth Singh, Roberto Aguero +3
Compressed vision-language models (VLMs) are widely used to reduce memory and compute costs, making them a suitable choice for real-world deployment. However, compressing these mod…
cs.CV2025
Bias-Aware Machine Unlearning: Towards Fairer Vision Models via Controllable Forgetting
Sai Siddhartha Chary Aylapuram, Veeraraju Elluru, Shivang Agarwal
Deep neural networks often rely on spurious correlations in training data, leading to biased or unfair predictions in safety-critical domains such as medicine and autonomous drivin…
cs.CL2024
Zero-resource Speech Translation and Recognition with LLMs
Karel Mundnich, Xing Niu, Prashant Mathur +10
Despite recent advancements in speech processing, zero-resource speech translation (ST) and automatic speech recognition (ASR) remain challenging problems. In this work, we propose…