2 citations · 5 across the 15 of their papers we have counts for
8 papers · 1 filter
Do Astronomical Foundation Models Know When They Will Fail?
Vaidehi Bulusu, Mehul Goyal, Md Rabius Sany Apu +2
Astronomical foundation models are increasingly used as reusable representations across surveys, but it is unclear when the same object remains consistently represented across inst…
Gestalt: a meta-foundation model for astronomy
Michael J. Smith, Shashwat Sourav
The Platonic Representation Hypothesis predicts that sufficiently scaled foundation models converge on a shared representation of the world. As each non-converged model gives a noi…
What AstroPT knows about galaxies, and what that can teach us about LLMs
UniverseTBD, :, Kshitij Duraphe +3
Interpretability research increasingly asks when concepts emerge during training and whether linear probes recover real structure, but in language models these claims are hard to v…
Visualizing Graph-to-Answer Mechanism Recovery in Materials-Science Hypothesis Generation
Shashwat Sourav, Subhadeep Pal, Markus J. Buehler +4
AI co-scientists can generate fluent materials-science hypotheses, but fluency does not show that an answer preserves a scientifically meaningful mechanism. We present a graph-to-a…
The Tell-Tale Trace: Detecting Reasoning Failures in LLMs Using Chain-of-Thought Dynamics
Shashwat Sourav, Aishwarya Balwani
Chain-of-thought (CoT) reasoning improves large language model (LLM) performance while also providing an observable interface to the model's reasoning process. Existing approaches…
Graph-Native Reinforcement Learning Enables Traceable Scientific Hypothesis Generation through Conceptual Recombination
Subhadeep Pal, Shashwat Sourav, Tirthankar Ghosal +1
Accelerating materials discovery requires AI systems that can generate scientifically valid hypotheses through multi-step, domain-grounded reasoning. Standard large language models…
Matter to Mechanism: A Benchmark for AI Co-Scientists in Materials and Battery Research
Shashwat Sourav, Tanjin. He, Maria K. Y. Chan +2
AI co-scientists are increasingly used for scientific discovery, but current evaluations still do not test them on a key task: moving from a concrete scientific or technological pr…
The Compressive Knowledge Graph Hypothesis: Which Graph Facts Matter for Scientific Hypothesis Generation?
Shashwat Sourav, Viktoriia Baibakova, Sanjay Das +4
Knowledge graphs (KGs) can provide structured scientific context to language models, but it remains unclear which graph facts actually shape the generated hypotheses. We study KG-g…