8 citations · 18 across the 8 of their papers we have counts for
4 papers · 1 filter
Teaching LLMs to Speak Spectroscopy
Nesar Ramachandra, Yuan-Sen Ting, Zechang Sun +2
Pre-trained Large Language Models (LLMs) have revolutionized text processing, yet adapting Transformer-based neural networks to non-textual scientific modalities typically requires…
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 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…
AstroMLab 1: Who Wins Astronomy Jeopardy!?
Yuan-Sen Ting, Tuan Dung Nguyen, Tirthankar Ghosal +8
We present a comprehensive evaluation of proprietary and open-weights large language models using the first astronomy-specific benchmarking dataset. This dataset comprises 4,425 mu…