14 citations · 40 across the 31 of their papers we have counts for
11 papers · 1 filter
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:…
HARNESS: Human-Agent Risk Navigation and Event Safety System for Proactive Hazard Forecasting in High-Risk DOE Environments
Ran Elgedawy, Sanjay Das, Ethan Seefried +7
Operational safety at mission-critical work sites is a top priority given the complex and hazardous nature of daily tasks. This paper presents the Human-Agent Risk Navigation and E…
ORCHID: Orchestrated Retrieval-Augmented Classification with Human-in-the-Loop Intelligent Decision-Making for High-Risk Property
Maria Mahbub, Vanessa Lama, Sanjay Das +6
High-Risk Property (HRP) classification is critical at U.S. Department of Energy (DOE) sites, where inventories include sensitive and often dual-use equipment. Compliance must trac…
Findings of the Third Automatic Minuting (AutoMin) Challenge
Kartik Shinde, Laurent Besacier, Ondrej Bojar +2
This paper presents the third edition of AutoMin, a shared task on automatic meeting summarization into minutes. In 2025, AutoMin featured the main task of minuting, the creation o…
Intelligent Manufacturing Support: Specialized LLMs for Composite Material Processing and Equipment Operation
Gunnika Kapoor, Komal Chawla, Tirthankar Ghosal +6
Engineering educational curriculum and standards cover many material and manufacturing options. However, engineers and designers are often unfamiliar with certain composite materia…
EPIC: Generative AI Platform for Accelerating HPC Operational Data Analytics
Ahmad Maroof Karimi, Woong Shin, Jesse Hines +3
We present EPIC, an AI-driven platform designed to augment operational data analytics. EPIC employs a hierarchical multi-agent architecture where a top-level large language model p…
PROV-AGENT: Unified Provenance for Tracking AI Agent Interactions in Agentic Workflows
Renan Souza, Amal Gueroudji, Stephen DeWitt +5
Large Language Models (LLMs) and other foundation models are increasingly used as the core of AI agents. In agentic workflows, these agents plan tasks, interact with humans and pee…
A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions
Agada Joseph Oche, Ademola Glory Folashade, Tirthankar Ghosal +1
Retrieval-Augmented Generation (RAG) represents a major advancement in natural language processing (NLP), combining large language models (LLMs) with information retrieval systems…
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…
Sparks of Science: Hypothesis Generation Using Structured Paper Data
Charles O'Neill, Tirthankar Ghosal, Roberta Răileanu +4
Generating novel and creative scientific hypotheses is a cornerstone in achieving Artificial General Intelligence. Large language and reasoning models have the potential to aid in…
A Survey on Hypothesis Generation for Scientific Discovery in the Era of Large Language Models
Atilla Kaan Alkan, Shashwat Sourav, Maja Jablonska +14
Hypothesis generation is a fundamental step in scientific discovery, yet it is increasingly challenged by information overload and disciplinary fragmentation. Recent advances in La…