5 citations · 5 across the 6 of their papers we have counts for
5 papers · 1 filter
Behaviour analysis for large language model-driven agents
Tianqiang Yan, Lizhen Qu
Understanding language-agent behaviour requires learning how actions are organised across a trajectory and how this organisation relates to context and outcomes. We propose a gener…
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: Causality-Inspired Behavior Analysis for Understanding the Self-Reflection of Language Models
Tianqiang Yan, Lizhen Qu, Sihan Shang +6
Self-reflection is a basic self-improvement skill of language agents, yet it does not reliably improve their outputs, where the underlying behavioral mechanism remains opaque. We i…