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Large language models (LLMs) have shown remarkable potential in various domains, but they often lack the ability to access and reason over domain-specific knowledge and tools.
KNIME: The Konstanz Information Miner
Michael R. Berthold, Nicolas Cebron, Fabian Dill, Thomas R. Gabriel, Tobias Kötter, Thorsten Meinl, Peter Ohl, Christoph Sieb, Kilian Thiel, and Bernd Wiswedel · 2007
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Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences
Jeremy Goecks, Anton Nekrutenko, James Taylor, and Team The Galaxy · 2010
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Rdkit: A software suite for cheminformatics, computational chemistry, and predictive modeling
Greg Landrum et al · 2013
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Chembl web services: streamlining access to drug discovery data and utilities
Mark Davies, Michał Nowotka, George Papadatos, Nathan Dedman, Anna Gaulton, Francis Atkinson, Louisa Bellis, and John P Overington · 2015
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A boiled-egg to predict gastrointestinal absorption and brain penetration of small molecules
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Perspective: Materials informatics and big data: Realization of the “fourth paradigm” of science in materials science
Ankit Agrawal and Alok Choudhary · 2016
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Machine learning for heterogeneous catalyst design and discovery
Bryan R. Goldsmith, Jacques Esterhuizen, Jin-Xun Liu, Christopher J. Bartel, and Christopher Sutton · 2018
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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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Transformers: State-of-the-Art Natural Language Processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Remi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander Rush · 2020
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Scipy 1.0: fundamental algorithms for scientific computing in python
Pauli Virtanen, Ralf Gommers, Travis E Oliphant, Matt Haberland, Tyler Reddy, David Cournapeau, Evgeni Burovski, Pearu Peterson, Warren Weckesser, Jonathan Bright, et al · 2020
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Zinc20—a free ultralarge-scale chemical database for ligand discovery
John J Irwin, Khanh G Tang, Jennifer Young, Chinzorig Dandarchuluun, Benjamin R Wong, Munkhzul Khurelbaatar, Yurii S Moroz, John Mayfield, and Roger A Sayle · 2020
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On the opportunities and risks of foundation models
Rishi Bommasani, Drew A Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, et al · 2021
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Artificial Intelligence for Autonomous Molecular Design: A Perspective
Rajendra P. Joshi and Neeraj Kumar · 2021
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Could graph neural networks learn better molecular representation for drug discovery? a comparison study of descriptor-based and graph-based models
Dejun Jiang, Zhenxing Wu, Chang-Yu Hsieh, Guangyong Chen, Ben Liao, Zhe Wang, Chao Shen, Dongsheng Cao, Jian Wu, and Tingjun Hou · 2021
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TALM: Tool Augmented Language Models, may 2022
Aaron Parisi, Yao Zhao, and Noah Fiedel · 2022
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LangChain, October 2022
Harrison Chase · 2022
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Ehud Karpas, Omri Abend, Yonatan Belinkov, Barak Lenz, Opher Lieber, Nir Ratner, Yoav Shoham, Hofit Bata, Yoav Levine, Kevin Leyton-Brown, et al · 2022
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ReAct: Synergizing Reasoning and Acting in Language Models, oct 2022
Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, and Yuan Cao · 2022
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De novo design of protein target specific scaffold-based Inhibitors via Reinforcement Learning
Andrew D. McNaughton, Mridula S. Bontha, Carter R. Knutson, Jenna A. Pope, and Neeraj Kumar · 2022
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Decoding the protein–ligand interactions using parallel graph neural networks
AQ Jiang, A Sablayrolles, A Mensch, C Bamford, DS Chaplot, D de las Casas, F Bressand, G Lengyel, G Lample, L Saulnier, et al · 2023
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Judging llm-as-a-judge with mt-bench and chatbot arena. arxiv preprint arxiv: 230605685
L Zheng, WL Chiang, Y Sheng, S Zhuang, Z Wu, Y Zhuang, Z Lin, Z Li, D Li, and E Xing · 2023
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Emergent autonomous scientific research capabilities of large language models, 2023
Daniil A. Boiko, Robert MacKnight, and Gabe Gomes · 2023
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Chemcrow: Augmenting large-language models with chemistry tools, 4 2023
Andres M Bran, Sam Cox, Andrew D White, and Philippe Schwaller · 2023
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Pubchem 2023 update
Sunghwan Kim, Jie Chen, Tiejun Cheng, Asta Gindulyte, Jia He, Siqian He, Qingliang Li, Benjamin A Shoemaker, Paul A Thiessen, Bo Yu, et al · 2023
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alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Carter Knutson, Mridula Bontha, Jenna A Bilbrey, and Neeraj Kumar · 2022
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Sabrina Chiesurin, Dimitris Dimakopoulos, Marco Antonio Sobrevilla Cabezudo, Arash Eshghi, Ioannis Papaioannou, Verena Rieser, and Ioannis Konstas · 2023
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Augmented language models: a survey, 2023
Grégoire Mialon, Roberto Dessì, Maria Lomeli, Christoforos Nalmpantis, Ram Pasunuru, Roberta Raileanu, Baptiste Rozière, Timo Schick, Jane Dwivedi-Yu, Asli Celikyilmaz, Edouard Grave, Yann LeCun, and Thomas Scialom · 2023
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On the tool manipulation capability of open-source large language models, 2023
Qiantong Xu, Fenglu Hong, Bo Li, Changran Hu, Zhengyu Chen, and Jian Zhang · 2023
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Toolllm: Facilitating large language models to master 16000+ real-world apis, 2023
Yujia Qin, Shihao Liang, Yining Ye, Kunlun Zhu, Lan Yan, Yaxi Lu, Yankai Lin, Xin Cong, Xiangru Tang, Bill Qian, Sihan Zhao, Lauren Hong, Runchu Tian, Ruobing Xie, Jie Zhou, Mark Gerstein, Dahai Li, Zhiyuan Liu, and Maosong Sun · 2023
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Large language models as tool makers, 5 2023
Tianle Cai, Xuezhi Wang, Tengyu Ma, Xinyun Chen, and Denny Zhou · 2023
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Large language models cannot self-correct reasoning yet
Jie Huang, Xinyun Chen, Swaroop Mishra, Huaixiu Steven Zheng, Adams Wei Yu, Xinying Song, and Denny Zhou · 2023
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Gpt-4 technical report, 2023
OpenAI · 2023
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Api-bank: A comprehensive benchmark for tool-augmented llms, 2023
Minghao Li, Yingxiu Zhao, Bowen Yu, Feifan Song, Hangyu Li, Haiyang Yu, Zhoujun Li, Fei Huang, and Yongbin Li · 2023
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Tooltalk: Evaluating tool-usage in a conversational setting, 2023
Nicholas Farn and Richard Shin · 2023
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https://github.com/Gentopia-AI/Gentopia , 2023
Gentopia · 2023
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Gpt understands, too
Xiao Liu, Yanan Zheng, Zhengxiao Du, Ming Ding, Yujie Qian, Zhilin Yang, and Jie Tang · 2023
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Ai-accelerated design of targeted covalent inhibitors for sars-cov-2
Rajendra P Joshi, Katherine J Schultz, Jesse William Wilson, Agustin Kruel, Rohith Anand Varikoti, Chathuri J Kombala, Daniel W Kneller, Stephanie Galanie, Gwyndalyn Phillips, Qiu Zhang, et al · 2023
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Integrated data-driven and experimental approaches to accelerate lead optimization targeting sars-cov-2 main protease
Rohith Anand Varikoti, Katherine J Schultz, Chathuri J Kombala, Agustin Kruel, Kristoffer R Brandvold, Mowei Zhou, and Neeraj Kumar · 2023
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Can large language models reason and plan?
Subbarao Kambhampati · 2024
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Gemma: Open models based on gemini research and technology
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Chatbot arena: An open platform for evaluating llms by human preference
Wei-Lin Chiang, Lianmin Zheng, Ying Sheng, Anastasios Nikolas Angelopoulos, Tianle Li, Dacheng Li, Hao Zhang, Banghua Zhu, Michael Jordan, Joseph E Gonzalez, et al · 2024
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