most citedA Survey on Hypothesis Generation for Scientific Discovery in the Era of Large Language Models

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cs.CL2025

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…

cs.CL20259 cited

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…

cs.CL20251 cited

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…

cs.CL20252 cited

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…

cs.CL2023

When Reviewers Lock Horn: Finding Disagreement in Scientific Peer Reviews

Sandeep Kumar, Tirthankar Ghosal, Asif Ekbal

To this date, the efficacy of the scientific publishing enterprise fundamentally rests on the strength of the peer review process. The journal editor or the conference chair primar…