most citedHiPerRAG: High-Performance Retrieval Augmented Generation for Scientific Insights

8 citations · 18 across the 8 of their papers we have counts for

collaborators

8 papers

astro-ph.GA2025

Multi-modal Foundation Model for Cosmological Simulation Data

Bin Xia, Nesar Ramachandra, Azton I. Wells +2

We present a multi-modal foundation model for astrophysical galaxy data, designed to map between simulation- and observation-based galactic features. Our encoder-only transformer f…

cs.CL2025★ 3 cited

Context Length Alone Hurts LLM Performance Despite Perfect Retrieval

Yufeng Du, Minyang Tian, Srikanth Ronanki +7

Large language models (LLMs) often fail to scale their performance on long-context tasks performance in line with the context lengths they support. This gap is commonly attributed…

astro-ph.IM2025

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…

cs.IR2025★ 8 cited

HiPerRAG: High-Performance Retrieval Augmented Generation for Scientific Insights

Ozan Gokdemir, Carlo Siebenschuh, Alexander Brace +21

The volume of scientific literature is growing exponentially, leading to underutilized discoveries, duplicated efforts, and limited cross-disciplinary collaboration. Retrieval Augm…

astro-ph.IM2025

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…

cs.AI2025★ 1 cited

EAIRA: Establishing a Methodology for Evaluating AI Models as Scientific Research Assistants

Franck Cappello, Sandeep Madireddy, Robert Underwood +23

Recent advancements have positioned AI, and particularly Large Language Models (LLMs), as transformative tools for scientific research, capable of addressing complex tasks that req…

astro-ph.IM2024★ 5 cited

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…

astro-ph.IM2024★ 1 cited

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…