Selected publications

I am interested in solving Computer Vision, Computer Audition, and Machine Learning problems and applying them to broad AI applications. My research focuses on applying multi-modal learning (Vision + X) for generative modeling and holistic cross-modal understanding with minimal supervision. In the past, I have focused on computational photography, tackling challenges such as image reflection removal, intrinsic image decomposition, inverse rendering and video quality assessment. Representative papers are highlighted. For full list of publications, please refer to my Google Scholar.

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

AURELIA: Test-time Reasoning Distillation in Audio-Visual LLMs

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

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

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

Towards Determining Perceived Human Intent for Multimodal Social Media Posts using The Theory of Reasoned Action

ASPIRE: Language-Guided Data Augmentation for Improving Robustness Against Spurious Correlations

Can LLM’s Generate Human-Like Wayfinding Instructions? Towards Platform-Agnostic Embodied Instruction Synthesis

MeLFusion: Synthesizing Music from Image and Language Cues using Diffusion Models (Highlight, Top 2.8%)

APoLLo : Unified Adapter and Prompt Learning for Vision Language Models

AdVerb: Visually Guided Audio Dereverberation

Measured Albedo in the Wild: Filling the Gap in Intrinsics Evaluation

AudViSum: Self-Supervised Deep Reinforcement Learning for Diverse Audio-Visual Summary Generation

V-DESIRR: Very Fast Deep Embedded Single Image Reflection Removal

Listen to the Pixels