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20232026
most citedPromptRefine: Enhancing Few-Shot Performance on Low-Resource Indic Languages with Example Selection from Related Example Banks

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cs.CV2025

EgoAdapt: Adaptive Multisensory Distillation and Policy Learning for Efficient Egocentric Perception

Sanjoy Chowdhury, Subrata Biswas, Sayan Nag +7

Modern perception models, particularly those designed for multisensory egocentric tasks, have achieved remarkable performance but often come with substantial computational costs. T…

cs.CV2025

MAGNET: A Multi-agent Framework for Finding Audio-Visual Needles by Reasoning over Multi-Video Haystacks

Sanjoy Chowdhury, Mohamed Elmoghany, Yohan Abeysinghe +5

Large multimodal models (LMMs) have shown remarkable progress in audio-visual understanding, yet they struggle with real-world scenarios that require complex reasoning across exten…

cs.CV2025

How Learnable Grids Recover Fine Detail in Low Dimensions: A Neural Tangent Kernel Analysis of Multigrid Parametric Encodings

Samuel Audia, Soheil Feizi, Matthias Zwicker +1

Neural networks that map between low dimensional spaces are ubiquitous in computer graphics and scientific computing; however, in their naive implementation, they are unable to lea…

cs.CV2025

AVTrustBench: Assessing and Enhancing Reliability and Robustness in Audio-Visual LLMs

Sanjoy Chowdhury, Sayan Nag, Subhrajyoti Dasgupta +4

With the rapid advancement of Multi-modal Large Language Models (MLLMs), several diagnostic benchmarks have recently been developed to assess these models' multi-modal reasoning pr…

cs.CV2024

Meerkat: Audio-Visual Large Language Model for Grounding in Space and Time

Sanjoy Chowdhury, Sayan Nag, Subhrajyoti Dasgupta +4

Leveraging Large Language Models' remarkable proficiency in text-based tasks, recent works on Multi-modal LLMs (MLLMs) extend them to other modalities like vision and audio. Howeve…

cs.CV2024

IntCoOp: Interpretability-Aware Vision-Language Prompt Tuning

Soumya Suvra Ghosal, Samyadeep Basu, Soheil Feizi +1

Image-text contrastive models such as CLIP learn transferable and robust representations for zero-shot transfer to a variety of downstream tasks. However, to obtain strong downstre…