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Foundation models are increasingly used in scientific research, but evaluating AI-generated scientific work remains challenging.
Dropout: a simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey E. Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov. 2014 · 1958
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Values of games with a priori unions
Guilliermo Owen. 1977 · 1977
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Latent dirichlet allocation
David M. Blei, Andrew Y. Ng, and Michael I. Jordan. 2003 · 2003
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NLTK: the natural language toolkit
Steven Bird. 2006 · 2006
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Models for predicting and explaining citation count of biomedical articles
Lawrence D. Fu and Constantin F. Aliferis. 2008 · 2008
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Predicting citation count of Bioinformatics papers within four years of publication
Alfonso Ibáñez, Pedro Larrañaga, and Concha Bielza. 2009 · 2009
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Rectified linear units improve restricted boltzmann machines
Vinod Nair and Geoffrey E. Hinton. 2010 · 2010
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Software Framework for Topic Modelling with Large Corpora
Radim Řehůřek and Petr Sojka. 2010 · 2010
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A unified approach to interpreting model predictions
Scott M. Lundberg and Su-In Lee. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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A dataset of peer reviews (peerread): Collection, insights and NLP applications
Dongyeop Kang, Waleed Ammar, Bhavana Dalvi, Madeleine van Zuylen, Sebastian Kohlmeier, Eduard H. Hovy, and Roy Schwartz. 2018 · 2018
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Predicting the citations of scholarly paper
Xiaomei Bai, Fuli Zhang, and Ivan Lee. 2019 · 2019
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A neural citation count prediction model based on peer review text
Siqing Li, Wayne Xin Zhao, Eddy Jing Yin, and Ji-Rong Wen. 2019 · 2019
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Citetracked: A longitudinal dataset of peer reviews and citations
Barbara Plank and Reinard van Dalen. 2019 · 2019
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Schubert: Scholarly document chunks with bert-encoding boost citation count prediction
Thomas van Dongen, Gideon Maillette de Buy Wenniger, and Lambert Schomaker. 2020 · 2020
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Peerassist: Leveraging on paper-review interactions to predict peer review decisions
Prabhat Kumar Bharti, Shashi Ranjan, Tirthankar Ghosal, Mayank Agrawal, and Asif Ekbal. 2021 · 2021
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What have we learned from openreview?
Gang Wang, Qi Peng, Yanfeng Zhang, and Mingyang Zhang. 2021a · 2021
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Coauthor: Designing a human-ai collaborative writing dataset for exploring language model capabilities
Mina Lee, Percy Liang, and Qian Yang. 2022 · 2022
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Benchmark for research theme classification of scholarly documents
Óscar E. Mendoza, Wojciech Kusa, Alaa El-Ebshihy, Ronin Wu, David Pride, Petr Knoth, Drahomira Herrmannova, Florina Piroi, Gabriella Pasi, and Allan Hanbury. 2022 · 2022
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Exploiting labeled and unlabeled data via transformer fine-tuning for peer-review score prediction
Panitan Muangkammuen, Fumiyo Fukumoto, Jiyi Li, and Yoshimi Suzuki. 2022 · 2022
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Can we automate scientific reviewing?
Weizhe Yuan, Pengfei Liu, and Graham Neubig. 2022 · 2022
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Autonomous chemical research with large language models
Daniil A. Boiko, Robert MacKnight, Ben Kline, and Gabe Gomes. 2023 · 2023
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Scirepeval: A multi-format benchmark for scientific document representations
Amanpreet Singh, Mike D’Arcy, Arman Cohan, Doug Downey, and Sergey Feldman. 2023 · 2023
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Jinheon Baek, Sujay Kumar Jauhar, Silviu Cucerzan, and Sung Ju Hwang. 2024 · 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 · 2024
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MARG: multi-agent review generation for scientific papers
Mike D’Arcy, Tom Hope, Larry Birnbaum, and Doug Downey. 2024 · 2024
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Scaling rectified flow transformers for high-resolution image synthesis
Patrick Esser, Sumith Kulal, Andreas Blattmann, Rahim Entezari, Jonas Müller, Harry Saini, Yam Levi, Dominik Lorenz, Axel Sauer, Frederic Boesel, Dustin Podell, Tim Dockhorn, Zion English, and Robin Rombach. 2024 · 2024
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Gideon Maillette de Buy Wenniger, Thomas van Dongen, and Lambert Schomaker. 2023 · 2023
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Palm-e: An embodied multimodal language model
Danny Driess, Fei Xia, Mehdi S. M. Sajjadi, Corey Lynch, Aakanksha Chowdhery, Brian Ichter, Ayzaan Wahid, Jonathan Tompson, Quan Vuong, Tianhe Yu, Wenlong Huang, Yevgen Chebotar, Pierre Sermanet, Daniel Duckworth, Sergey Levine, Vincent Vanhoucke, Karol Hausman, Marc Toussaint, Klaus Greff, Andy Zeng, Igor Mordatch, and Pete Florence. 2023 · 2023
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Nlpeer: A unified resource for the computational study of peer review
Nils Dycke, Ilia Kuznetsov, and Iryna Gurevych. 2023 · 2023
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Citebench: A benchmark for scientific citation text generation
Martin Funkquist, Ilia Kuznetsov, Yufang Hou, and Iryna Gurevych. 2023 · 2023
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Enabling large language models to generate text with citations
Tianyu Gao, Howard Yen, Jiatong Yu, and Danqi Chen. 2023 · 2023
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Realistic citation count prediction task for newly published papers
Jun Hirako, Ryohei Sasano, and Koichi Takeda. 2023 · 2023
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A dataset on malicious paper bidding in peer review
Steven Jecmen, Minji Yoon, Vincent Conitzer, Nihar B. Shah, and Fei Fang. 2023 · 2023
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Enhancing the examination of obstacles in an automated peer review system
Gustavo Lúcius Fernandes and Pedro O. S. Vaz de Melo. 2024 · 2024
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Cimate: Citation count prediction effectively leveraging the main text
Jun Hirako, Ryohei Sasano, and Koichi Takeda. 2024 · 2024
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Predicting citation impact of research papers using GPT and other text embeddings
Adilson Vital Jr., Filipi N. Silva, Osvaldo N. Oliveira Jr., and Diego R. Amancio. 2024 · 2024
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Mlr-copilot: Autonomous machine learning research based on large language models agents
Ruochen Li, Teerth Patel, Qingyun Wang, and Xinya Du. 2024 · 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 · 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 · 2024
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An analysis of tasks and datasets in peer reviewing
Moritz Staudinger, Wojciech Kusa, Florina Piroi, and Allan Hanbury. 2024 · 2024
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Scimon: Scientific inspiration machines optimized for novelty
Qingyun Wang, Doug Downey, Heng Ji, and Tom Hope. 2024 · 2024
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Large language models for automated open-domain scientific hypotheses discovery
Zonglin Yang, Xinya Du, Junxian Li, Jie Zheng, Soujanya Poria, and Erik Cambria. 2024 · 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 · 2024
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Is LLM a reliable reviewer? A comprehensive evaluation of LLM on automatic paper reviewing tasks
Ruiyang Zhou, Lu Chen, and Kai Yu. 2024 · 2024
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