17 citations · 29 across the 19 of their papers we have counts for
7 papers · 2 filters
Are Large Language Models Good Classifiers? A Study on Edit Intent Classification in Scientific Document Revisions
Qian Ruan, Ilia Kuznetsov, Iryna Gurevych
Classification is a core NLP task architecture with many potential applications. While large language models (LLMs) have brought substantial advancements in text generation, their…
STRICTA: Structured Reasoning in Critical Text Assessment for Peer Review and Beyond
Nils Dycke, Matej Zečević, Ilia Kuznetsov +3
Critical text assessment is at the core of many expert activities, such as fact-checking, peer review, and essay grading. Yet, existing work treats critical text assessment as a bl…
Systematic Task Exploration with LLMs: A Study in Citation Text Generation
Furkan Şahinuç, Ilia Kuznetsov, Yufang Hou +1
Large language models (LLMs) bring unprecedented flexibility in defining and executing complex, creative natural language generation (NLG) tasks. Yet, this flexibility brings new c…
M2QA: Multi-domain Multilingual Question Answering
Leon Engländer, Hannah Sterz, Clifton Poth +3
Generalization and robustness to input variation are core desiderata of machine learning research. Language varies along several axes, most importantly, language instance (e.g. Fre…
Re3: A Holistic Framework and Dataset for Modeling Collaborative Document Revision
Qian Ruan, Ilia Kuznetsov, Iryna Gurevych
Collaborative review and revision of textual documents is the core of knowledge work and a promising target for empirical analysis and NLP assistance. Yet, a holistic framework tha…
What Can Natural Language Processing Do for Peer Review?
Ilia Kuznetsov, Osama Mohammed Afzal, Koen Dercksen +21
The number of scientific articles produced every year is growing rapidly. Providing quality control over them is crucial for scientists and, ultimately, for the public good. In mod…