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The spread of scientific knowledge depends on how researchers discover and cite previous work.
Networks of scientific papers: The pattern of bibliographic references indicates the nature of the scientific research front
Derek J De Solla Price · 1965
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Knowledge: Its Creation, Distribution, and Economic Significance, Volume I: Knowledge and Knowledge Production
Fritz Machlup · 1980
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Does automation bias decision-making?
Linda J Skitka, Kathleen L Mosier, and Mark Burdick · 1999
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Read before you cite!
Mikhail V Simkin and Vwani P Roychowdhury · 2002
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The politics of publication
Peter A Lawrence · 2003
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What do citation counts measure? a review of studies on citing behavior
Lutz Bornmann and Hans-Dieter Daniel · 2008
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Electronic publication and the narrowing of science and scholarship
James A Evans · 2008
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Universality of citation distributions: Toward an objective measure of scientific impact
Filippo Radicchi, Santo Fortunato, and Claudio Castellano · 2008
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Introduction to information retrieval
Hinrich Schütze, Christopher D Manning, and Prabhakar Raghavan · 2008
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How citation distortions create unfounded authority: analysis of a citation network
Steven A Greenberg · 2009
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The impact factor’s matthew effect: A natural experiment in bibliometrics
Vincent Larivière and Yves Gingras · 2010
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Investigating different types of research collaboration and citation impact: a case study of harvard university’s publications
Ali Gazni and Fereshteh Didegah · 2011
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The data matching process
Peter Christen and Peter Christen · 2012
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Impact factors, scientometrics and the history of citation-based research
Derek R Smith · 2012
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Quantifying long-term scientific impact
Dashun Wang, Chaoming Song, and Albert-László Barabási · 2013
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Citation time window choice for research impact evaluation
Jian Wang · 2013
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Unpacking the Matthew effect in citations
Jian Wang · 2014
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The advantage of short paper titles
Adrian Letchford, Helen Susannah Moat, and Tobias Preis · 2015
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Factors affecting number of citations: a comprehensive review of the literature
Iman Tahamtan, Askar Safipour Afshar, and Khadijeh Ahamdzadeh · 2016
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Think you have solved question answering? try arc, the ai2 reasoning challenge
Peter Clark, Isaac Cowhey, Oren Etzioni, Tushar Khot, Ashish Sabharwal, Carissa Schoenick, and Oyvind Tafjord · 2018
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Science of science
Santo Fortunato, Carl T Bergstrom, Katy Börner, James A Evans, Dirk Helbing, Staša Milojević, Alexander M Petersen, Filippo Radicchi, Roberta Sinatra, Brian Uzzi, et al · 2018
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Core elements in the process of citing publications: Conceptual overview of the literature
Iman Tahamtan and Lutz Bornmann · 2018
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Document co-citation analysis to enhance transdisciplinary research
Caleb M. Trujillo and Tammy M. Long · 2018
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Large teams develop and small teams disrupt science and technology
Lingfei Wu, Dashun Wang, and James A Evans · 2019
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Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
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Measuring massive multitask language understanding
Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt · 2020
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Retrieval-augmented generation for knowledge-intensive nlp tasks
Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, et al · 2020
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How much is too much? the difference between research influence and self-citation excess
Martin Szomszor, David A. Pendlebury, and Jonathan Adams · 2020
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Ai-assisted peer review
Alessandro Checco, Lorenzo Bracciale, Pierpaolo Loreti, Stephen Pinfield, and Giuseppe Bianchi · 2021
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Evaluating large language models trained on code
Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde De Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, et al · 2021
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Training verifiers to solve math word problems
Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, et al · 2021
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Measuring mathematical problem solving with the math dataset
Dan Hendrycks, Collin Burns, Saurav Kadavath, Akul Arora, Steven Basart, Eric Tang, Dawn Song, and Jacob Steinhardt · 2021
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Impact of the reference list features on the number of citations
Stefano Mammola, Diego Fontaneto, Alejandro Martínez, and Filipe Chichorro · 2021
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Global citation inequality is on the rise
Mathias Wullum Nielsen and Jens Peter Andersen · 2021
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Automated citation recommendation tools encourage questionable citations
Serge PJM Horbach, Freek JW Oude Maatman, Willem Halffman, and Wytske M Hepkema · 2022
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Language models (mostly) know what they know
Saurav Kadavath, Tom Conerly, Amanda Askell, Tom Henighan, Dawn Drain, Ethan Perez, Nicholas Schiefer, Zac Hatfield-Dodds, Nova DasSarma, Eli Tran-Johnson, et al · 2022
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Large language models are zero-shot reasoners
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa · 2022
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Matryoshka representation learning
Aditya Kusupati, Gantavya Bhatt, Aniket Rege, Matthew Wallingford, Aditya Sinha, Vivek Ramanujan, William Howard-Snyder, Kaifeng Chen, Sham Kakade, Prateek Jain, et al · 2022
Cited alongside, same era.
Beyond the imitation game: Quantifying and extrapolating the capabilities of language models
Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, Abu Awal Md Shoeb, Abubakar Abid, Adam Fisch, Adam R Brown, Adam Santoro, Aditya Gupta, Adrià Garriga-Alonso, et al · 2022
Cited alongside, same era.
Self-consistency improves chain of thought reasoning in language models
Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc Le, Ed Chi, Sharan Narang, Aakanksha Chowdhery, and Denny Zhou · 2022
Cited alongside, same era.
Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al · 2022
Cited alongside, same era.
Large language models show human-like content biases in transmission chain experiments
How to optimize the systematic review process using ai tools
Nicholas Fabiano, Arnav Gupta, Nishaant Bhambra, Brandon Luu, Stanley Wong, Muhammad Maaz, Jess G Fiedorowicz, Andrew L Smith, and Marco Solmi · 2024
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Sciagents: Automating scientific discovery through multi-agent intelligent graph reasoning
Alireza Ghafarollahi and Markus J Buehler · 2024
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Testing the reliability of an ai-based large language model to extract ecological information from the scientific literature
Andrew V Gougherty and Hannah L Clipp · 2024
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Language models represent space and time
Wes Gurnee and Max Tegmark · 2024
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Mining causality: Ai-assisted search for instrumental variables
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Alberto Acerbi and Joseph M Stubbersfield · 2023
Cited alongside, same era.
Beyond citations: Measuring novel scientific ideas and their impact in publication text
Sam Arts, Nicola Melluso, and Reinhilde Veugelers · 2023
Cited alongside, same era.
Emergent autonomous scientific research capabilities of large language models
Daniil A Boiko, Robert MacKnight, and Gabe Gomes · 2023
Cited alongside, same era.
Sparks of artificial general intelligence: Early experiments with gpt-4
Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan, Johannes Gehrke, Eric Horvitz, Ece Kamar, Peter Lee, Yin Tat Lee, Yuanzhi Li, Scott Lundberg, et al · 2023
Cited alongside, same era.
Enabling large language models to generate text with citations
Tianyu Gao, Howard Yen, Jiatong Yu, and Danqi Chen · 2023
Cited alongside, same era.
Reasoning with language model is planning with world model
Shibo Hao, Yi Gu, Haodi Ma, Joshua Jiahua Hong, Zhen Wang, Daisy Zhe Wang, and Zhiting Hu · 2023
Cited alongside, same era.
Large language models for automated data science: Introducing caafe for context-aware automated feature engineering
Noah Hollmann, Samuel Müller, and Frank Hutter · 2023
Cited alongside, same era.
Lei Huang, Weijiang Yu, Weitao Ma, Weihong Zhong, Zhangyin Feng, Haotian Wang, Qianglong Chen, Weihua Peng, Xiaocheng Feng, Bing Qin, et al · 2023
Cited alongside, same era.
Sukjin Han · 2024
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Predicting results of social science experiments using large language models
Luke Hewitt, Ashwini Ashokkumar, Isaias Ghezae, and Robb Willer · 2024
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Dataset artefacts are the hidden drivers of the declining disruptiveness in science
Vincent Holst, Andres Algaba, Floriano Tori, Sylvia Wenmackers, and Vincent Ginis · 2024
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SWE-bench: Can language models resolve real-world github issues?
Carlos E Jimenez, John Yang, Alexander Wettig, Shunyu Yao, Kexin Pei, Ofir Press, and Karthik R Narasimhan · 2024
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Researcharena: Benchmarking llms’ ability to collect and organize information as research agents
Hao Kang and Chenyan Xiong · 2024
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Chatgpt as research scientist: Probing gpt’s capabilities as a research librarian, research ethicist, data generator, and data predictor
Steven A. Lehr, Aylin Caliskan, Suneragiri Liyanage, and Mahzarin R. Banaji · 2024
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Scilitllm: How to adapt llms for scientific literature understanding
Sihang Li, Jin Huang, Jiaxi Zhuang, Yaorui Shi, Xiaochen Cai, Mingjun Xu, Xiang Wang, Linfeng Zhang, Guolin Ke, and Hengxing Cai · 2024
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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
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Augmenting large language models with chemistry tools
Andres M. Bran, Sam Cox, Oliver Schilter, Carlo Baldassari, Andrew D White, and Philippe Schwaller · 2024
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Automated social science: Language models as scientist and subjects
Benjamin S. Manning, Kehang Zhu, and John J. Horton · 2024
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Use of large language models as artificial intelligence tools in academic research and publishing among global clinical researchers
Tanisha Mishra, Edward Sutanto, Rini Rossanti, Nayana Pant, Anum Ashraf, Akshay Raut, Germaine Uwabareze, Ajayi Oluwatomiwa, and Bushra Zeeshan · 2024
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CiteME: Can language models accurately cite scientific claims?
Ori Press, Andreas Hochlehnert, Ameya Prabhu, Vishaal Udandarao, Ofir Press, and Matthias Bethge · 2024
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Mathematical discoveries from program search with large language models
Bernardino Romera-Paredes, Mohammadamin Barekatain, Alexander Novikov, Matej Balog, M Pawan Kumar, Emilien Dupont, Francisco JR Ruiz, Jordan S Ellenberg, Pengming Wang, Omar Fawzi, et al · 2024
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Is something rotten in the state of denmark? cross-national evidence for widespread involvement but not systematic use of questionable research practices across all fields of research
Jesper W Schneider, Nick Allum, Jens Peter Andersen, Michael Bang Petersen, Emil B Madsen, Niels Mejlgaard, and Robert Zachariae · 2024
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Can llms generate novel research ideas? a large-scale human study with 100+ nlp researchers
Chenglei Si, Diyi Yang, and Tatsunori Hashimoto · 2024
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Language agents achieve superhuman synthesis of scientific knowledge
Michael D Skarlinski, Sam Cox, Jon M Laurent, James D Braza, Michaela Hinks, Michael J Hammerling, Manvitha Ponnapati, Samuel G Rodriques, and Andrew D White · 2024
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Automating research synthesis with domain-specific large language model fine-tuning
Teo Susnjak, Peter Hwang, Napoleon H Reyes, Andre LC Barczak, Timothy R McIntosh, and Surangika Ranathunga · 2024
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The virtual lab: Ai agents design new sars-cov-2 nanobodies with experimental validation
Kyle Swanson, Wesley Wu, Nash L Bulaong, John E Pak, and James Zou · 2024
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Zhi Rui Tam, Cheng-Kuang Wu, Yi-Lin Tsai, Chieh-Yen Lin, Hung-yi Lee, and Yun-Nung Chen · 2024
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Do llms exhibit human-like response biases? a case study in survey design
Lindia Tjuatja, Valerie Chen, Tongshuang Wu, Ameet Talwalkwar, and Graham Neubig · 2024
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Solving olympiad geometry without human demonstrations
Trieu H Trinh, Yuhuai Wu, Quoc V Le, He He, and Thang Luong · 2024
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Tree of thoughts: Deliberate problem solving with large language models
Shunyu Yao, Dian Yu, Jeffrey Zhao, Izhak Shafran, Tom Griffiths, Yuan Cao, and Karthik Narasimhan · 2024
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Predicting citation impact of academic papers across research areas using multiple models and early citations
Fang Zhang and Shengli Wu · 2024
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Can large language models transform computational social science?
Caleb Ziems, William Held, Omar Shaikh, Jiaao Chen, Zhehao Zhang, and Diyi Yang · 2024
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Unveiling the power of language models in chemical research question answering
Xiuying Chen, Tairan Wang, Taicheng Guo, Kehan Guo, Juexiao Zhou, Haoyang Li, Zirui Song, Xin Gao, and Xiangliang Zhang · 2025
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Transforming literature screening: The emerging role of large language models in systematic reviews
Fernando M. Delgado-Chaves, Matthew J. Jennings, Antonio Atalaia, Justus Wolff, Rita Horvath, Zeinab M. Mamdouh, Jan Baumbach, and Linda Baumbach · 2025
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Juraj Gottweis, Wei-Hung Weng, Alexander Daryin, Tao Tu, Anil Palepu, Petar Sirkovic, Artiom Myaskovsky, Felix Weissenberger, Keran Rong, Ryutaro Tanno, et al · 2025
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Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning
Daya Guo, Dejian Yang, Haowei Zhang, Junxiao Song, Ruoyu Zhang, Runxin Xu, Qihao Zhu, Shirong Ma, Peiyi Wang, Xiao Bi, et al · 2025
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How deeply do llms internalize human citation practices? a graph-structural and embedding-based evaluation
Melika Mobini, Vincent Holst, Floriano Tori, Andres Algaba, and Vincent Ginis · 2025
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Niklas Muennighoff, Zitong Yang, Weijia Shi, Xiang Lisa Li, Li Fei-Fei, Hannaneh Hajishirzi, Luke Zettlemoyer, Percy Liang, Emmanuel Candès, and Tatsunori Hashimoto · 2025
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Long Phan, Alice Gatti, Ziwen Han, Nathaniel Li, Josephina Hu, Hugh Zhang, Sean Shi, Michael Choi, Anish Agrawal, Arnav Chopra, et al · 2025
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Agent laboratory: Using llm agents as research assistants
Samuel Schmidgall, Yusheng Su, Ze Wang, Ximeng Sun, Jialian Wu, Xiaodong Yu, Jiang Liu, Zicheng Liu, and Emad Barsoum · 2025
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Large language models for scientific discovery in molecular property prediction
Yizhen Zheng, Huan Yee Koh, Jiaxin Ju, Anh TN Nguyen, Lauren T May, Geoffrey I Webb, and Shirui Pan · 2025
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