collaborators

16 papers

cs.CV2026

Reasoning-Guided Part-Level Visual Grounding via Reinforcement Learning

Kazi Sajeed Mehrab, Hani Alomari, Najibul Haque Sarker +4

Multimodal large language models (MLLMs) ground whole objects well from free-form language queries, but they struggle when the query names a part rather than the object. We trace t…

cs.LG2026

LakeFM: Toward a Foundation Model for Aquatic Ecosystems Using Irregular Multivariate Multi-depth Time Series Data

Abhilash Neog, Sepideh Fatemi, Medha Sawhney +9

Understanding and forecasting lake dynamics is critical for monitoring water quality and ecosystem health across lakes and reservoirs. While machine learning methods have been rece…

cs.CV2026

SeamCam: Quantifying Seamless Camouflage via Multi-Cue Visual Detectability

Amin Karimi Monsefi, Abolfazl Meyarian, Mridul Khurana +6

Animals are described as effectively camouflaged when they blend seamlessly with their surrounding, yet no standardized quantitative measure of this seamlessness exists. We address…

cs.CV2026

TaxaAdapter: Vision Taxonomy Models are Key to Fine-grained Image Generation over the Tree of Life

Mridul Khurana, Amin Karimi Monsefi, Justin Lee +9

Accurately generating images across the Tree of Life is difficult: there are over 10M distinct species on Earth, many of which differ only by subtle visual traits. Despite the rema…

cs.IR2026

VILLA: Versatile Information Retrieval From Scientific Literature Using Large LAnguage Models

Blessy Antony, Amartya Dutta, Sneha Aggarwal +7

The lack of high-quality ground truth datasets to train machine learning (ML) models impedes the potential of artificial intelligence (AI) for science research. Scientific informat…

cs.CV2026

A continental-scale dataset of ground beetles with high-resolution images and validated morphological trait measurements

S M Rayeed, Mridul Khurana, Alyson East +18

Despite the ecological significance of invertebrates, global trait databases remain heavily biased toward vertebrates and plants, limiting comprehensive ecological analyses of high…