4 papers
Rethinking Domain Specialization for Open-Ended Scientific Reasoning in Astronomy Language Models
Vanessa Lama, Sanjay Das, Emily Herron +5
Domain-specialized language models are widely used for scientific question answering, but stronger general-purpose systems raise a sharper question: when does domain-specific fine-…
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…
SciTrust 2.0: A Comprehensive Framework for Evaluating Trustworthiness of Large Language Models in Scientific Applications
Emily Herron, Junqi Yin, Feiyi Wang
Large language models (LLMs) have demonstrated transformative potential in scientific research, yet their deployment in high-stakes contexts raises significant trustworthiness conc…
AstroMLab 4: Benchmark-Topping Performance in Astronomy Q&A with a 70B-Parameter Domain-Specialized Reasoning Model
Tijmen de Haan, Yuan-Sen Ting, Tirthankar Ghosal +7
General-purpose large language models (LLMs), despite their broad capabilities, often struggle with specialized domain knowledge. This gap hinders their deployment as reliable rese…