activity
20242026
collaborators

5 papers

cs.AI2026

Land cover and flood type govern the detection limits of satellite-based flood mapping across diverse global flood events

Venkatesh Kolluru, Rajat Shinde, Abdelhak Marouane +6

Floods are among the most destructive natural hazards, and their increasing frequency under climate change makes satellite-based inundation mapping essential for disaster response.…

cs.CE2025

Toward Open Earth Science as Fast and Accessible as Natural Language

Marquita Ellis, Iksha Gurung, Muthukumaran Ramasubramanian +1

Is natural-language-driven earth observation data analysis now feasible with the assistance of Large Language Models (LLMs)? For open science in service of public interest, feasibi…

astro-ph.SR2025

SuryaBench: Benchmark Dataset for Advancing Machine Learning in Heliophysics and Space Weather Prediction

Sujit Roy, Dinesha V. Hegde, Johannes Schmude +22

This paper introduces a high resolution, machine learning-ready heliophysics dataset derived from NASA's Solar Dynamics Observatory (SDO), specifically designed to advance machine…

cs.AI2024

Challenges in Guardrailing Large Language Models for Science

Nishan Pantha, Muthukumaran Ramasubramanian, Iksha Gurung +2

The rapid development in large language models (LLMs) has transformed the landscape of natural language processing and understanding (NLP/NLU), offering significant benefits across…

cs.CL2024

INDUS: Effective and Efficient Language Models for Scientific Applications

Bishwaranjan Bhattacharjee, Aashka Trivedi, Masayasu Muraoka +33

Large language models (LLMs) trained on general domain corpora showed remarkable results on natural language processing (NLP) tasks. However, previous research demonstrated LLMs tr…