6 papers
ReGround: Grounding Reviewer Comments in Multimodal Evidence
Serwar Basch, Lizhen Qu, Iryna Gurevych
Reviewer comments naturally relate to specific parts of the reviewed paper, yet grounding these comments to the underlying evidence is difficult due to long multimodal documents. E…
Judgment-Grounded Expansion for Peer Review Generation
Sheng Lu, Lizhen Qu, Iryna Gurevych
Automatic review generation is a promising direction for accelerating scientific progress. While most work adopts an end-to-end setup, its fully automated nature makes it less suit…
Reviewing the Reviewer: LLM-Assisted Reviewer Feedback Generation for Guideline Compliance
Sukannya Purkayastha, Qile Wan, Anne Lauscher +2
Peer review is central to scientific quality, yet reliance on simple heuristics, namely lazy thinking and non-specific critiques, has threatened review quality. Prior work frames l…
ReBeCA: Unveiling Interpretable Behavior Hierarchy behind the Iterative Self-Reflection of Language Models with Causal Analysis
Tianqiang Yan, Lizhen Qu, Sihan Shang +6
While self-reflection can enhance language model reliability, its underlying mechanisms remain opaque, with existing analyses often yielding correlation-based insights that fail to…
LazyReview A Dataset for Uncovering Lazy Thinking in NLP Peer Reviews
Sukannya Purkayastha, Zhuang Li, Anne Lauscher +2
Peer review is a cornerstone of quality control in scientific publishing. With the increasing workload, the unintended use of `quick' heuristics, referred to as lazy thinking, has…
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…