12 citations · 22 across the 5 of their papers we have counts for
4 papers · 1 filter
Impact of large language models on peer review opinions from a fine-grained perspective: Evidence from top conference proceedings in AI
Wenqing Wu, Chengzhi Zhang, Yi Zhao +1
With the rapid advancement of Large Language Models (LLMs), the academic community has faced unprecedented disruptions, particularly in the realm of academic communication. The pri…
NovBench: Evaluating Large Language Models on Academic Paper Novelty Assessment
Wenqing Wu, Yi Zhao, Yuzhuo Wang +4
Novelty is a core requirement in academic publishing and a central focus of peer review, yet the growing volume of submissions has placed increasing pressure on human reviewers. Wh…
SC4ANM: Identifying Optimal Section Combinations for Automated Novelty Prediction in Academic Papers
Wenqing Wu, Chengzhi Zhang, Tong Bao +1
Novelty is a core component of academic papers, and there are multiple perspectives on the assessment of novelty. Existing methods often focus on word or entity combinations, which…
Are the confidence scores of reviewers consistent with the review content? Evidence from top conference proceedings in AI
Wenqing Wu, Haixu Xi, Chengzhi Zhang
Peer review is vital in academia for evaluating research quality. Top AI conferences use reviewer confidence scores to ensure review reliability, but existing studies lack fine-gra…