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Scientific problem-solving involves synthesizing information while applying expert knowledge.
Materials properties handbook: titanium alloys
Gerhard Welsch, Rodney Boyer, and EW Collings · 1993
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Handbook of materials selection
Myer Kutz · 2002
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Genia corpus—a semantically annotated corpus for bio-textmining
J-D Kim, Tomoko Ohta, Yuka Tateisi, and Jun’ichi Tsujii · 2003
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Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin · 2004
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A class of quantum ldpc codes: construction and performances under iterative decoding
Thomas Camara, Harold Ollivier, and Jean-Pierre Tillich · 2007
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Biopython: freely available python tools for computational molecular biology and bioinformatics
Peter JA Cock, Tiago Antao, Jeffrey T Chang, Brad A Chapman, Cymon J Cox, Andrew Dalke, Iddo Friedberg, Thomas Hamelryck, Frank Kauff, Bartek Wilczynski, et al · 2009
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The utility of google trends for epidemiological research: Lyme disease as an example
Ari Seifter, Alison Schwarzwalder, Kate Geis, and John Aucott · 2010
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Fault-tolerant measurement-based quantum computing with continuous-variable cluster states
Nicolas C. Menicucci · 2014
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Chemprot-3.0: a global chemical biology diseases mapping
Jens Kringelum, Sonny Kim Kjaerulff, Søren Brunak, Ole Lund, Tudor I Oprea, and Olivier Taboureau · 2016
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Biocreative v cdr task corpus: a resource for chemical disease relation extraction
Jiao Li, Yueping Sun, Robin J Johnson, Daniela Sciaky, Chih-Hsuan Wei, Robert Leaman, Allan Peter Davis, Carolyn J Mattingly, Thomas C Wiegers, and Zhiyong Lu · 2016
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Chemdataextractor: a toolkit for automated extraction of chemical information from the scientific literature
Matthew C Swain and Jacqueline M Cole · 2016
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https://docs.materialsproject.org/methodology/materials-methodology/electronic-structure-accuracy-of-band-structures, 2017
Materialsproject.org · 2017
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Monitoring pertussis infections using internet search queries
Yuzhou Zhang, Gabriel Milinovich, Zhiwei Xu, Hilary Bambrick, Kerrie Mengersen, Shilu Tong, and Wenbiao Hu · 2017
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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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Measuring the evolution of a scientific field through citation frames
David Jurgens, Srijan Kumar, Raine Hoover, Dan McFarland, and Dan Jurafsky · 2018
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The narrativeqa reading comprehension challenge
Tomáš Kočiskỳ, Jonathan Schwarz, Phil Blunsom, Chris Dyer, Karl Moritz Hermann, Gábor Melis, and Edward Grefenstette · 2018
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Multi-task identification of entities, relations, and coreference for scientific knowledge graph construction
Yi Luan, Luheng He, Mari Ostendorf, and Hannaneh Hajishirzi · 2018
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A corpus with multi-level annotations of patients, interventions and outcomes to support language processing for medical literature
Benjamin Nye, Junyi Jessy Li, Roma Patel, Yinfei Yang, Iain J Marshall, Ani Nenkova, and Byron C Wallace · 2018
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Scibert: A pretrained language model for scientific text
Iz Beltagy, Kyle Lo, and Arman Cohan · 2019
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Structural scaffolds for citation intent classification in scientific publications
Arman Cohan, Waleed Ammar, Madeleine Van Zuylen, and Field Cady · 2019
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Drop: A reading comprehension benchmark requiring discrete reasoning over paragraphs
Dheeru Dua, Yizhong Wang, Pradeep Dasigi, Gabriel Stanovsky, Sameer Singh, and Matt Gardner · 2019
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Pubmedqa: A dataset for biomedical research question answering
Qiao Jin, Bhuwan Dhingra, Zhengping Liu, William Cohen, and Xinghua Lu · 2019
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Hellaswag: Can a machine really finish your sentence?
Rowan Zellers, Ari Holtzman, Yonatan Bisk, Ali Farhadi, and Yejin Choi · 2019
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Bertscore: Evaluating text generation with bert
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q Weinberger, and Yoav Artzi · 2019
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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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Bioasq at clef2020: Large-scale biomedical semantic indexing and question answering
Martin Krallinger, Anastasia Krithara, Anastasios Nentidis, Georgios Paliouras, and Marta Villegas · 2020
Gpqa: A graduate-level google-proof q&a benchmark
David Rein, Betty Li Hou, Asa Cooper Stickland, Jackson Petty, Richard Yuanzhe Pang, Julien Dirani, Julian Michael, and Samuel R Bowman · 2023
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Zeroscrolls: A zero-shot benchmark for long text understanding
Uri Shaham, Maor Ivgi, Avia Efrat, Jonathan Berant, and Omer Levy · 2023
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Xiang Zhang, Zichun Zhou, Chen Ming, and Yi-Yang Sun · 2023
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Chatgpt chemistry assistant for text mining and prediction of mof synthesis
Zhiling Zheng, Oufan Zhang, Christian Borgs, Jennifer T Chayes, and Omar M Yaghi · 2023
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alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
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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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A dataset of information-seeking questions and answers anchored in research papers
Pradeep Dasigi, Kyle Lo, Iz Beltagy, Arman Cohan, Noah A Smith, and Matt Gardner · 2021
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Domain-specific language model pretraining for biomedical natural language processing
Yu Gu, Robert Tinn, Hao Cheng, Michael Lucas, Naoto Usuyama, Xiaodong Liu, Tristan Naumann, Jianfeng Gao, and Hoifung Poon · 2021
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Booksum: A collection of datasets for long-form narrative summarization
Wojciech Kryściński, Nazneen Rajani, Divyansh Agarwal, Caiming Xiong, and Dragomir Radev · 2021
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Time-series snowmelt detection over the antarctic using sentinel-1 sar images on google earth engine
Dong Liang, Huadong Guo, Lu Zhang, Yun Cheng, Qi Zhu, and Xuting Liu · 2021
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Structured information extraction from complex scientific text with fine-tuned large language models
Alexander Dunn, John Dagdelen, Nicholas Walker, Sanghoon Lee, Andrew S Rosen, Gerbrand Ceder, Kristin Persson, and Anubhav Jain · 2022
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L-eval: Instituting standardized evaluation for long context language models
Chenxin An, Shansan Gong, Ming Zhong, Mukai Li, Jun Zhang, Lingpeng Kong, and Xipeng Qiu · 2023
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Victor V. Albert and Philippe Faist (eds.) · 2024
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Data science at the singularity
David Donoho · 2024
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Ruler: What’s the real context size of your long-context language models?
Cheng-Ping Hsieh, Simeng Sun, Samuel Kriman, Shantanu Acharya, Dima Rekesh, Fei Jia, and Boris Ginsburg · 2024
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Albert Q Jiang, Alexandre Sablayrolles, Antoine Roux, Arthur Mensch, Blanche Savary, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Emma Bou Hanna, Florian Bressand, et al · 2024
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Prometheus-vision: Vision-language model as a judge for fine-grained evaluation
Seongyun Lee, Seungone Kim, Sue Hyun Park, Geewook Kim, and Minjoon Seo · 2024
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Lost in the middle: How language models use long contexts
Nelson F Liu, Kevin Lin, John Hewitt, Ashwin Paranjape, Michele Bevilacqua, Fabio Petroni, and Percy Liang · 2024
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Improving automatic vqa evaluation using large language models
Oscar Mañas, Benno Krojer, and Aishwarya Agrawal · 2024
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On the Evaluation of Machine-Generated Reports, May 2024
James Mayfield, Eugene Yang, Dawn Lawrie, Sean MacAvaney, Paul McNamee, Douglas W. Oard, Luca Soldaini, Ian Soboroff, Orion Weller, Efsun Kayi, Kate Sanders, Marc Mason, and Noah Hibbler · 2024
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Quantum many-body physics calculations with large language models
Haining Pan, Nayantara Mudur, Will Taranto, Maria Tikhanovskaya, Subhashini Venugopalan, Yasaman Bahri, Michael P. Brenner, and Eun-Ah Kim · 2024
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Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Machel Reid, Nikolay Savinov, Denis Teplyashin, Dmitry Lepikhin, Timothy Lillicrap, Jean-baptiste Alayrac, Radu Soricut, Angeliki Lazaridou, Orhan Firat, Julian Schrittwieser, et al · 2024
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Focused transformer: Contrastive training for context scaling
Szymon Tworkowski, Konrad Staniszewski, Mikołaj Pacek, Yuhuai Wu, Henryk Michalewski, and Piotr Miłoś · 2024
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Ada-leval: Evaluating long-context llms with length-adaptable benchmarks
Chonghua Wang, Haodong Duan, Songyang Zhang, Dahua Lin, and Kai Chen · 2024
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MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?
Renrui Zhang, Dongzhi Jiang, Yichi Zhang, Haokun Lin, Ziyu Guo, Pengshuo Qiu, Aojun Zhou, Pan Lu, Kai-Wei Chang, Peng Gao, et al · 2024
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Judging llm-as-a-judge with mt-bench and chatbot arena
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric Xing, et al · 2024
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Lima: Less is more for alignment
Chunting Zhou, Pengfei Liu, Puxin Xu, Srinivasan Iyer, Jiao Sun, Yuning Mao, Xuezhe Ma, Avia Efrat, Ping Yu, Lili Yu, et al · 2024
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Fanoutqa: Multi-hop, multi-document question answering for large language models
Andrew Zhu, Alyssa Hwang, Liam Dugan, and Chris Callison-Burch · 2024
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