Fetching the paper…
Reading the bibliography…
Scholarly peer review is a cornerstone of scientific advancement, but the system is under strain due to increasing manuscript submissions and the labor-intensive nature of the process.
Conditional logit analysis of qualitative choice behavior
D MCFADDEN · 1974
Earlier work this paper cites.
Peerless science: Peer review and US science policy
Daryl E Chubin and Edward J Hackett · 1990
Earlier work this paper cites.
Addressing the curse of imbalanced training sets: one-sided selection
Miroslav Kubat, Stan Matwin, et al · 1997
Earlier work this paper cites.
Peer review: a flawed process at the heart of science and journals
Richard Smith · 2006
Earlier work this paper cites.
Is peer review broken? submissions are up, reviewers are overtaxed, and authors are lodging complaint after complaint about the process at top-tier journals. what’s wrong with peer review?
Alison McCook · 2006
Earlier work this paper cites.
An introduction to roc analysis
Tom Fawcett · 2006
Earlier work this paper cites.
Reviewing peer review, 2008
Bruce Alberts, Brooks Hanson, and Katrina L Kelner · 2008
Earlier work this paper cites.
Learning from imbalanced data
Haibo He and Edwardo A Garcia · 2009
Earlier work this paper cites.
Bias in peer review
Carole J Lee, Cassidy R Sugimoto, Guo Zhang, and Blaise Cronin · 2013
Earlier work this paper cites.
Open access is tiring out peer reviewers
Martijn Arns · 2014
Earlier work this paper cites.
Why training and specialization is needed for peer review: a case study of peer review for randomized controlled trials
Jigisha Patel · 2014
Earlier work this paper cites.
Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references
Lutz Bornmann and Rüdiger Mutz · 2015
Earlier work this paper cites.
The global burden of journal peer review in the biomedical literature: Strong imbalance in the collective enterprise
Michail Kovanis, Raphaël Porcher, Philippe Ravaud, and Ludovic Trinquart · 2016
Earlier work this paper cites.
Recruitment of reviewers is becoming harder at some journals: a test of the influence of reviewer fatigue at six journals in ecology and evolution
Charles W Fox, Arianne YK Albert, and Timothy H Vines · 2017
Earlier work this paper cites.
Sciencebeam—using computer vision to extract pdf data
D Ecer and G Maciocci · 2017
Earlier work this paper cites.
The changing forms and expectations of peer review
SPJM ( Serge) Horbach and W ( Willem) Halffman · 2018
Earlier work this paper cites.
A billion-dollar donation: estimating the cost of researchers’ time spent on peer review
Balazs Aczel, Barnabas Szaszi, and Alex O Holcombe · 2021
Earlier work this paper cites.
Automated screening of covid-19 preprints: can we help authors to improve transparency and reproducibility?
Tracey Weissgerber, Nico Riedel, Halil Kilicoglu, Cyril Labbé, Peter Eckmann, Gerben Ter Riet, Jennifer Byrne, Guillaume Cabanac, Amanda Capes-Davis, Bertrand Favier, et al · 2021
Earlier work this paper cites.
Challenges, experiments, and computational solutions in peer review
Nihar B Shah · 2022
Cited alongside, same era.
Is the future of peer review automated?
Robert Schulz, Adrian Barnett, René Bernard, Nicholas JL Brown, Jennifer A Byrne, Peter Eckmann, Małgorzata A Gazda, Halil Kilicoglu, Eric M Prager, Maia Salholz-Hillel, et al · 2022
Cited alongside, same era.
Large pre-trained language models contain human-like biases of what is right and wrong to do
Patrick Schramowski, Cigdem Turan, Nico Andersen, Constantin A Rothkopf, and Kristian Kersting · 2022
Cited alongside, same era.
OpenAI · 2023
Cited alongside, same era.
Reviewergpt? an exploratory study on using large language models for paper reviewing
Ryan Liu and Nihar B Shah · 2023
Cited alongside, same era.
The ai scientist: Towards fully automated open-ended scientific discovery
Chris Lu, Cong Lu, Robert Tjarko Lange, Jakob Foerster, Jeff Clune, and David Ha · 2024
Closest in time.
AgentReview: Exploring peer review dynamics with LLM agents
Yiqiao Jin, Qinlin Zhao, Yiyang Wang, Hao Chen, Kaijie Zhu, Yijia Xiao, and Jindong Wang · 2024
Closest in time.
Automated peer reviewing in paper sea: Standardization, evaluation, and analysis
Jianxiang Yu, Zichen Ding, Jiaqi Tan, Kangyang Luo, Zhenmin Weng, Chenghua Gong, Long Zeng, RenJing Cui, Chengcheng Han, Qiushi Sun, et al · 2024
Closest in time.
Monitoring ai-modified content at scale: A case study on the impact of chatgpt on ai conference peer reviews
Weixin Liang, Zachary Izzo, Yaohui Zhang, Haley Lepp, Hancheng Cao, Xuandong Zhao, Lingjiao Chen, Haotian Ye, Sheng Liu, Zhi Huang, et al · 2024
Closest in time.
The ai review lottery: Widespread ai-assisted peer reviews boost paper scores and acceptance rates
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Fighting reviewer fatigue or amplifying bias? considerations and recommendations for use of chatgpt and other large language models in scholarly peer review
Mohammad Hosseini and Serge PJM Horbach · 2023
Cited alongside, same era.
Toxicity in chatgpt: Analyzing persona-assigned language models
Ameet Deshpande, Vishvak Murahari, Tanmay Rajpurohit, Ashwin Kalyan, and Karthik Narasimhan · 2023
Cited alongside, same era.
Defending chatgpt against jailbreak attack via self-reminders
Yueqi Xie, Jingwei Yi, Jiawei Shao, Justin Curl, Lingjuan Lyu, Qifeng Chen, Xing Xie, and Fangzhao Wu · 2023
Cited alongside, same era.
Siren’s song in the ai ocean: a survey on hallucination in large language models
Yue Zhang, Yafu Li, Leyang Cui, Deng Cai, Lemao Liu, Tingchen Fu, Xinting Huang, Enbo Zhao, Yu Zhang, Yulong Chen, et al · 2023
Cited alongside, same era.
Selfcheckgpt: Zero-resource black-box hallucination detection for generative large language models
Potsawee Manakul, Adian Liusie, and Mark Gales · 2023
Cited alongside, same era.
Large language models are not fair evaluators
Peiyi Wang, Lei Li, Liang Chen, Zefan Cai, Dawei Zhu, Binghuai Lin, Yunbo Cao, Qi Liu, Tianyu Liu, and Zhifang Sui · 2023
Cited alongside, same era.
Large language models are not robust multiple choice selectors
Chujie Zheng, Hao Zhou, Fandong Meng, Jie Zhou, and Minlie Huang · 2023
Cited alongside, same era.
Giuseppe Russo Latona, Manoel Horta Ribeiro, Tim R Davidson, Veniamin Veselovsky, and Robert West · 2024
Closest in time.
Is your paper being reviewed by an llm? investigating ai text detectability in peer review
Sungduk Yu, Man Luo, Avinash Madasu, Vasudev Lal, and Phillip Howard · 2024
Closest in time.
Yi Zeng, Hongpeng Lin, Jingwen Zhang, Diyi Yang, Ruoxi Jia, and Weiyan Shi · 2024
Closest in time.
Bias and fairness in large language models: A survey
Isabel O Gallegos, Ryan A Rossi, Joe Barrow, Md Mehrab Tanjim, Sungchul Kim, Franck Dernoncourt, Tong Yu, Ruiyi Zhang, and Nesreen K Ahmed · 2024
Closest in time.
Benchmarking cognitive biases in large language models as evaluators
Ryan Koo, Minhwa Lee, Vipul Raheja, Jong Inn Park, Zae Myung Kim, and Dongyeop Kang · 2024
Closest in time.
Cognitive bias in decision-making with LLMs
Jessica Maria Echterhoff, Yao Liu, Abeer Alessa, Julian McAuley, and Zexue He · 2024
Closest in time.
Paper checklist
NeurIPS · 2024
Closest in time.
Length-controlled alpacaeval: A simple way to debias automatic evaluators
Yann Dubois, Balázs Galambosi, Percy Liang, and Tatsunori B Hashimoto · 2024
Closest in time.
Deepseek-v2: A strong, economical, and efficient mixture-of-experts language model, 2024
DeepSeek-AI · 2024
Closest in time.
Qwen2.5: A party of foundation models, September 2024
Qwen Team · 2024
Closest in time.
Chatbot arena: An open platform for evaluating llms by human preference, 2024
Wei-Lin Chiang, Lianmin Zheng, Ying Sheng, Anastasios Nikolas Angelopoulos, Tianle Li, Dacheng Li, Hao Zhang, Banghua Zhu, Michael Jordan, Joseph E. Gonzalez, and Ion Stoica · 2024
Closest in time.
QS World University Rankings by Subject 2024: Computer Science & Information Systems, 2024
QS Top Universities · 2024
Closest in time.
Assisting iclr 2025 reviewers with feedback
ICLR · 2024
Closest in time.