15 citations · 18 across the 5 of their papers we have counts for
5 papers
Agentic AI Scientists Are Not Built For Autonomous Scientific Discovery
Harshit Bisht, Vinay Kumar, Kevin Maik Jablonka +2
A growing body of work pursues AI scientists capable of end-to-end autonomous scientific discovery. This position paper argues that although they already function as co-scientists,…
MDGYM: Benchmarking AI Agents on Molecular Simulations
Vinay Kumar, Satyendra Rajput, Mausam +1
The promise of AI-driven scientific discovery hinges on whether AI agents can autonomously design and execute the computational workflows that underpin modern science. Molecular dy…
MatSKRAFT: A framework for large-scale materials knowledge extraction from scientific tables
Kausik Hira, Mohd Zaki, Mausam +1
Scientific progress increasingly depends on synthesizing knowledge across vast literature, yet most experimental data remains trapped in semi-structured formats that resist systema…
Foundational Large Language Models for Materials Research
Vaibhav Mishra, Somaditya Singh, Dhruv Ahlawat +7
Materials discovery and development are critical for addressing global challenges. Yet, the exponential growth in materials science literature comprising vast amounts of textual da…
DiSCoMaT: Distantly Supervised Composition Extraction from Tables in Materials Science Articles
Tanishq Gupta, Mohd Zaki, Devanshi Khatsuriya +3
A crucial component in the curation of KB for a scientific domain (e.g., materials science, foods & nutrition, fuels) is information extraction from tables in the domain's publishe…