From the 1 of 28 linked papers with an AI index.
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Visualizing Graph-to-Answer Mechanism Recovery in Materials-Science Hypothesis Generation
Shashwat Sourav, Subhadeep Pal, Markus J. Buehler +4
AI co-scientists can generate fluent materials-science hypotheses, but fluency does not show that an answer preserves a scientifically meaningful mechanism. We present a graph-to-a…
Can Large Language Models Unlock Novel Scientific Research Ideas?
Sandeep Kumar, Tirthankar Ghosal, Vinayak Goyal +1
The widespread adoption of Large Language Models (LLMs) and publicly available ChatGPT have marked a significant turning point in the integration of Artificial Intelligence (AI) in…
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…
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…
Sparks of Science: Hypothesis Generation Using Structured Paper Data
Charles O'Neill, Tirthankar Ghosal, Roberta RÄileanu +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…