activity
20212026
most citedWhat Can Natural Language Processing Do for Peer Review?

5 citations · 9 across the 8 of their papers we have counts for

collaborators

9 papers

cs.CL2026

'Your AI Text is not Mine': Redefining and Evaluating AI-generated Text Detection under Realistic Assumptions

Nils Dycke, Marina Sakharova, Nico Daheim +1

Although it is generally agreed that AI-generated text poses a broad societal risk, there is no common understanding in the AI-generated text detection literature on what constitut…

cs.CL2025

Automatic Reviewers Fail to Detect Faulty Reasoning in Research Papers: A New Counterfactual Evaluation Framework

Nils Dycke, Iryna Gurevych

Large Language Models (LLMs) have great potential to accelerate and support scholarly peer review and are increasingly used as fully automatic review generators (ARGs). However, po…

cs.CL2025★ 1 cited

Decision-Making with Deliberation: Meta-reviewing as a Document-grounded Dialogue

Sukannya Purkayastha, Nils Dycke, Anne Lauscher +1

Meta-reviewing is a pivotal stage in the peer-review process, serving as the final step in determining whether a paper is recommended for acceptance. Prior research on meta-reviewi…

cs.CL2024

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…

cs.CL2024★ 5 cited

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…

cs.CL2023

CARE: Collaborative AI-Assisted Reading Environment

Dennis Zyska, Nils Dycke, Jan Buchmann +2

Recent years have seen impressive progress in AI-assisted writing, yet the developments in AI-assisted reading are lacking. We propose inline commentary as a natural vehicle for AI…

cs.CL2022★ 1 cited

NLPeer: A Unified Resource for the Computational Study of Peer Review

Nils Dycke, Ilia Kuznetsov, Iryna Gurevych

Peer review constitutes a core component of scholarly publishing; yet it demands substantial expertise and training, and is susceptible to errors and biases. Various applications o…

cs.CL2022

Yes-Yes-Yes: Proactive Data Collection for ACL Rolling Review and Beyond

Nils Dycke, Ilia Kuznetsov, Iryna Gurevych

The shift towards publicly available text sources has enabled language processing at unprecedented scale, yet leaves under-serviced the domains where public and openly licensed dat…

cs.CL2021★ 2 cited

Assisting Decision Making in Scholarly Peer Review: A Preference Learning Perspective

Nils Dycke, Edwin Simpson, Ilia Kuznetsov +1

Peer review is the primary means of quality control in academia; as an outcome of a peer review process, program and area chairs make acceptance decisions for each paper based on t…