6 papers
Predicting New Concept-Object Associations in Astronomy by Mining the Literature
Jinchu Li, Yuan-Sen Ting, Alberto Accomazzi +2
We construct a concept-object knowledge graph from the full astro-ph corpus through July 2025. Using an automated pipeline, we extract named astrophysical objects from OCR-processe…
Do Lexical and Contextual Coreference Resolution Systems Degrade Differently under Mention Noise? An Empirical Study on Scientific Software Mentions
Atilla Kaan Alkan, Felix Grezes, Jennifer Lynn Bartlett +3
We present our participation in the SOMD 2026 shared task on cross-document software mention coreference resolution, where our systems ranked second across all three subtasks. We c…
AstroConcepts: A Large-Scale Multi-Label Classification Corpus for Astrophysics
Atilla Kaan Alkan, Felix Grezes, Sergi Blanco-Cuaresma +5
Scientific multi-label text classification suffers from extreme class imbalance, where specialized terminology exhibits severe power-law distributions that challenge standard class…
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…
AstroMLab 5: Structured Summaries and Concept Extraction for 400,000 Astrophysics Papers
Yuan-Sen Ting, Alberto Accomazzi, Tirthankar Ghosal +4
We present a dataset of 408,590 astrophysics papers from arXiv (astro-ph), spanning 1992 through July 2025. Each paper has been processed through a multi-stage pipeline to produce:…
AstroMLab 3: Achieving GPT-4o Level Performance in Astronomy with a Specialized 8B-Parameter Large Language Model
Tijmen de Haan, Yuan-Sen Ting, Tirthankar Ghosal +6
AstroSage-Llama-3.1-8B is a domain-specialized natural-language AI assistant tailored for research in astronomy, astrophysics, cosmology, and astronomical instrumentation. Trained…