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Large Language Models (LLMs) have significantly transformed our daily life and established a new paradigm in natural language processing (NLP).
Strategies for pre-training graph neural networks
Weihua Hu, Bowen Liu, Joseph Gomes, Marinka Zitnik, Percy Liang, Vijay Pande, and Jure Leskovec. 2019 · 1905
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Usage and limitations of liquid chromatography-tandem mass spectrometry (lc-ms/ms) in clinical routine laboratories
Christoph Seger. 2012 · 1946
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The generation of a unique machine description for chemical structures-a technique developed at chemical abstracts service
Harry L Morgan. 1965 · 1965
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Smiles, a chemical language and information system. 1. introduction to methodology and encoding rules
David Weininger. 1988 · 1988
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Simple statistical gradient-following algorithms for connectionist reinforcement learning
Ronald J Williams. 1992 · 1992
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An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy. 2020 · 2010
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Large-pore apertures in a series of metal-organic frameworks
Hexiang Deng, Sergio Grunder, Kyle E Cordova, Cory Valente, Hiroyasu Furukawa, Mohamad Hmadeh, Felipe Gándara, Adam C Whalley, Zheng Liu, Shunsuke Asahina, et al. 2012 · 2012
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Nuclear magnetic resonance spectroscopy and its key role in environmental research
Andre J Simpson, Myrna J Simpson, and Ronald Soong. 2012 · 2012
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Inchi-the worldwide chemical structure identifier standard
Stephen Heller, Alan McNaught, Stephen Stein, Dmitrii Tchekhovskoi, and Igor Pletnev. 2013 · 2013
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Commentary: The materials project: A materials genome approach to accelerating materials innovation
Anubhav Jain, Shyue Ping Ong, Geoffroy Hautier, Wei Chen, William Davidson Richards, Stephen Dacek, Shreyas Cholia, Dan Gunter, David Skinner, Gerbrand Ceder, et al. 2013 · 2013
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Auto-encoding variational bayes
Diederik P Kingma. 2013 · 2013
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Metal–organic frameworks (mofs)
Susumu Kitagawa et al. 2014 · 2014
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Searching molecular structure databases with tandem mass spectra using csi: Fingerid
Kai Dührkop, Huibin Shen, Marvin Meusel, Juho Rousu, and Sebastian Böcker. 2015 · 2015
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Convolutional networks on graphs for learning molecular fingerprints
David K Duvenaud, Dougal Maclaurin, Jorge Iparraguirre, Rafael Bombarell, Timothy Hirzel, Alán Aspuru-Guzik, and Ryan P Adams. 2015 · 2015
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Neural machine translation of rare words with subword units
Rico Sennrich. 2015 · 2015
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Zinc 15–ligand discovery for everyone
Teague Sterling and John J Irwin. 2015 · 2015
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Deep reinforcement learning from human preferences
Paul F Christiano, Jan Leike, Tom Brown, Miljan Martic, Shane Legg, and Dario Amodei. 2017 · 2017
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Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Crowdsourcing multiple choice science questions
Johannes Welbl, Nelson F Liu, and Matt Gardner. 2017 · 2017
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin. 2018 · 2018
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Schnet–a deep learning architecture for molecules and materials
Kristof T Schütt, Huziel E Sauceda, P-J Kindermans, Alexandre Tkatchenko, and K-R Müller. 2018 · 2018
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Planning chemical syntheses with deep neural networks and symbolic ai
Marwin HS Segler, Mike Preuss, and Mark P Waller. 2018 · 2018
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Moleculenet: a benchmark for molecular machine learning
Zhenqin Wu, Bharath Ramsundar, Evan N Feinberg, Joseph Gomes, Caleb Geniesse, Aneesh S Pappu, Karl Leswing, and Vijay Pande. 2018 · 2018
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How powerful are graph neural networks?
Keyulu Xu, Weihua Hu, Jure Leskovec, and Stefanie Jegelka. 2018 · 2018
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Pubchem 2019 update: improved access to chemical data
Sunghwan Kim, Jie Chen, Tiejun Cheng, Asta Gindulyte, Jia He, Siqian He, Qingliang Li, Benjamin A Shoemaker, Paul A Thiessen, Bo Yu, et al. 2019 · 2019
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N-gram graph: Simple unsupervised representation for graphs, with applications to molecules
Shengchao Liu, Mehmet F Demirel, and Yingyu Liang. 2019 · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al. 2019 · 2019
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Self-referencing embedded strings (selfies): A 100% robust molecular string representation
Mario Krenn, Florian Häse, AkshatKumar Nigam, Pascal Friederich, and Alan Aspuru-Guzik. 2020 · 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 · 2020
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Transfer learning enables the molecular transformer to predict regio-and stereoselective reactions on carbohydrates
Giorgio Pesciullesi, Philippe Schwaller, Teodoro Laino, and Jean-Louis Reymond. 2020 · 2020
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu. 2020 · 2020
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Learning to summarize with human feedback
Nisan Stiennon, Long Ouyang, Jeffrey Wu, Daniel Ziegler, Ryan Lowe, Chelsea Voss, Alec Radford, Dario Amodei, and Paul F Christiano. 2020 · 2020
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Geometric deep learning on molecular representations
Kenneth Atz, Francesca Grisoni, and Gisbert Schneider. 2021 · 2021
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Img2mol–accurate smiles recognition from molecular graphical depictions
Djork-Arné Clevert, Tuan Le, Robin Winter, and Floriane Montanari. 2021 · 2021
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Text2mol: Cross-modal molecule retrieval with natural language queries
Carl Edwards, ChengXiang Zhai, and Heng Ji. 2021 · 2021
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Swin transformer: Hierarchical vision transformer using shifted windows
Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo. 2021 · 2021
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E (n) equivariant graph neural networks
Vıctor Garcia Satorras, Emiel Hoogeboom, and Max Welling. 2021 · 2021
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Cfm-id 4.0: more accurate esi-ms/ms spectral prediction and compound identification
Fei Wang, Jaanus Liigand, Siyang Tian, David Arndt, Russell Greiner, and David S Wishart. 2021 · 2021
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Chemberta-2: Towards chemical foundation models
Walid Ahmad, Elana Simon, Seyone Chithrananda, Gabriel Grand, and Bharath Ramsundar. 2022 · 2022
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Flamingo: a visual language model for few-shot learning
Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, Antoine Miech, Iain Barr, Yana Hasson, Karel Lenc, Arthur Mensch, Katherine Millican, Malcolm Reynolds, et al. 2022 · 2022
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Constitutional ai: Harmlessness from ai feedback
Yuntao Bai, Saurav Kadavath, Sandipan Kundu, Amanda Askell, Jackson Kernion, Andy Jones, Anna Chen, Anna Goldie, Azalia Mirhoseini, Cameron McKinnon, et al. 2022 · 2022
Cited alongside, same era.
Translation between molecules and natural language
Carl Edwards, Tuan Lai, Kevin Ros, Garrett Honke, Kyunghyun Cho, and Heng Ji. 2022 · 2022
Cited alongside, same era.
Brio: Bringing order to abstractive summarization
Yixin Liu, Pengfei Liu, Dragomir Radev, and Graham Neubig. 2022 · 2022
Cited alongside, same era.
Learn to explain: Multimodal reasoning via thought chains for science question answering
Pan Lu, Swaroop Mishra, Tanglin Xia, Liang Qiu, Kai-Wei Chang, Song-Chun Zhu, Oyvind Tafjord, Peter Clark, and Ashwin Kalyan. 2022 · 2022
Cited alongside, same era.
Training language models to follow instructions with human feedback
Uni-mol: A universal 3d molecular representation learning framework
Gengmo Zhou, Zhifeng Gao, Qiankun Ding, Hang Zheng, Hongteng Xu, Zhewei Wei, Linfeng Zhang, and Guolin Ke. 2023 · 2023
Later among the works it cites.
Unraveling molecular structure: A multimodal spectroscopic dataset for chemistry
Marvin Alberts, Oliver Schilter, Federico Zipoli, Nina Hartrampf, and Teodoro Laino. 2024 · 2024
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Introducing claude models, https://www.anthropic.com
Anthropic. 2024 · 2024
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Massspecgym: A benchmark for the discovery and identification of molecules
Roman Bushuiev, Anton Bushuiev, Niek F de Jonge, Adamo Young, Fleming Kretschmer, Raman Samusevich, Janne Heirman, Fei Wang, Luke Zhang, Kai Dührkop, et al. 2024 · 2024
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Sciassess: Benchmarking llm proficiency in scientific literature analysis
alphaXiv searches the wider corpus for related work and actual follow-ups.
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Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al. 2022 · 2022
Cited alongside, same era.
Computational design of metal–organic frameworks with unprecedented high hydrogen working capacity and high synthesizability
Junkil Park, Yunsung Lim, Sangwon Lee, and Jihan Kim. 2022 · 2022
Cited alongside, same era.
Msnovelist: de novo structure generation from mass spectra
Michael A Stravs, Kai Dührkop, Sebastian Böcker, and Nicola Zamboni. 2022 · 2022
Cited alongside, same era.
A molecular multimodal foundation model associating molecule graphs with natural language
Bing Su, Dazhao Du, Zhao Yang, Yujie Zhou, Jiangmeng Li, Anyi Rao, Hao Sun, Zhiwu Lu, and Ji-Rong Wen. 2022 · 2022
Cited alongside, same era.
Galactica: A large language model for science
Ross Taylor, Marcin Kardas, Guillem Cucurull, Thomas Scialom, Anthony Hartshorn, Elvis Saravia, Andrew Poulton, Viktor Kerkez, and Robert Stojnic. 2022 · 2022
Cited alongside, same era.
A systematic survey of chemical pre-trained models
Jun Xia, Yanqiao Zhu, Yuanqi Du, and Stan Z Li. 2022 · 2022
Cited alongside, same era.
Decoupled self-supervised learning for graphs
Teng Xiao, Zhengyu Chen, Zhimeng Guo, Zeyang Zhuang, and Suhang Wang. 2022 · 2022
Cited alongside, same era.
React: Synergizing reasoning and acting in language models
Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, and Yuan Cao. 2022 · 2022
Cited alongside, same era.
Hengxing Cai, Xiaochen Cai, Junhan Chang, Sihang Li, Lin Yao, Changxin Wang, Zhifeng Gao, Yongge Li, Mujie Lin, Shuwen Yang, et al. 2024 · 2024
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Towards scalable automated alignment of llms: A survey
Boxi Cao, Keming Lu, Xinyu Lu, Jiawei Chen, Mengjie Ren, Hao Xiang, Peilin Liu, Yaojie Lu, Ben He, Xianpei Han, et al. 2024 · 2024
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Yuan Chiang, Chia-Hong Chou, and Janosh Riebesell. 2024 · 2024
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Structured information extraction from scientific text with large language models
John Dagdelen, Alexander Dunn, Sanghoon Lee, Nicholas Walker, Andrew S Rosen, Gerbrand Ceder, Kristin A Persson, and Anubhav Jain. 2024 · 2024
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Organa: A robotic assistant for automated chemistry experimentation and characterization
Kourosh Darvish, Marta Skreta, Yuchi Zhao, Naruki Yoshikawa, Sagnik Som, Miroslav Bogdanovic, Yang Cao, Han Hao, Haoping Xu, Alán Aspuru-Guzik, et al. 2024 · 2024
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K2: A foundation language model for geoscience knowledge understanding and utilization
Cheng Deng, Tianhang Zhang, Zhongmou He, Qiyuan Chen, Yuanyuan Shi, Yi Xu, Luoyi Fu, Weinan Zhang, Xinbing Wang, Chenghu Zhou, et al. 2024 · 2024
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Guanting Dong, Keming Lu, Chengpeng Li, Tingyu Xia, Bowen Yu, Chang Zhou, and Jingren Zhou. 2024 · 2024
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Developments and applications of the optimade api for materials discovery, design, and data exchange
Matthew Evans, Johan Bergsma, Andrius Merkys, Casper Andersen, Oskar B Andersson, Daniel Beltrán, Evgeny Blokhin, Tara M Boland, Rubén Castañeda Balderas, Kamal Choudhary, et al. 2024 · 2024
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Openchemie: An information extraction toolkit for chemistry literature
Vincent Fan, Yujie Qian, Alex Wang, Amber Wang, Connor W Coley, and Regina Barzilay. 2024 · 2024
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Sciknoweval: Evaluating multi-level scientific knowledge of large language models
Kehua Feng, Keyan Ding, Weijie Wang, Xiang Zhuang, Zeyuan Wang, Ming Qin, Yu Zhao, Jianhua Yao, Qiang Zhang, and Huajun Chen. 2024 · 2024
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Can llms solve molecule puzzles? a multimodal benchmark for molecular structure elucidation
Kehan Guo, Bozhao Nan, Yujun Zhou, Taicheng Guo, Zhichun Guo, Mihir Surve, Zhenwen Liang, Nitesh V Chawla, Olaf Wiest, and Xiangliang Zhang. 2024 · 2024
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De novo drug design using reinforcement learning with multiple gpt agents
Xiuyuan Hu, Guoqing Liu, Yang Zhao, and Hao Zhang. 2024 · 2024
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Large language models open new way of ai-assisted molecule design for chemists
Shoichi Ishida, Tomohiro Sato, Teruki Honma, and Kei Terayama. 2024 · 2024
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Leveraging large language models for predictive chemistry
Kevin Maik Jablonka, Philippe Schwaller, Andres Ortega-Guerrero, and Berend Smit. 2024 · 2024
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Language models in molecular discovery
Nikita Janakarajan, Tim Erdmann, Sarath Swaminathan, Teodoro Laino, and Jannis Born. 2024 · 2024
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Visscience: An extensive benchmark for evaluating k12 educational multi-modal scientific reasoning
Zhihuan Jiang, Zhen Yang, Jinhao Chen, Zhengxiao Du, Weihan Wang, Bin Xu, Yuxiao Dong, and Jie Tang. 2024 · 2024
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Chatmof: an artificial intelligence system for predicting and generating metal-organic frameworks using large language models
Yeonghun Kang and Jihan Kim. 2024 · 2024
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Molx: Enhancing large language models for molecular learning with a multi-modal extension
Khiem Le, Zhichun Guo, Kaiwen Dong, Xiaobao Huang, Bozhao Nan, Roshni Iyer, Xiangliang Zhang, Olaf Wiest, Wei Wang, and Nitesh V Chawla. 2024 · 2024
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From words to molecules: A survey of large language models in chemistry
Chang Liao, Yemin Yu, Yu Mei, and Ying Wei. 2024 · 2024
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nach0: Multimodal natural and chemical languages foundation model
Micha Livne, Zulfat Miftahutdinov, Elena Tutubalina, Maksim Kuznetsov, Daniil Polykovskiy, Annika Brundyn, Aastha Jhunjhunwala, Anthony Costa, Alex Aliper, Alán Aspuru-Guzik, et al. 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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Bridging chemical modalities by aligning embeddings
Adrian Mirza, Sebastian Starke, Erinc Merdivan, and Kevin Maik Jablonka. 2024 · 2024
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Direct preference optimization: Your language model is secretly a reward model
Rafael Rafailov, Archit Sharma, Eric Mitchell, Christopher D Manning, Stefano Ermon, and Chelsea Finn. 2024 · 2024
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A review of large language models and autonomous agents in chemistry
Mayk Caldas Ramos, Christopher J Collison, and Andrew D White. 2024 · 2024
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Toolformer: Language models can teach themselves to use tools
Timo Schick, Jane Dwivedi-Yu, Roberto Dessì, Roberta Raileanu, Maria Lomeli, Eric Hambro, Luke Zettlemoyer, Nicola Cancedda, and Thomas Scialom. 2024 · 2024
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Chemreasoner: Heuristic search over a large language model’s knowledge space using quantum-chemical feedback
Henry W Sprueill, Carl Edwards, Khushbu Agarwal, Mariefel V Olarte, Udishnu Sanyal, Conrad Johnston, Hongbin Liu, Heng Ji, and Sutanay Choudhury. 2024 · 2024
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Scieval: A multi-level large language model evaluation benchmark for scientific research
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Mollm: a unified language model for integrating biomedical text with 2d and 3d molecular representations
Xiangru Tang, Andrew Tran, Jeffrey Tan, and Mark B Gerstein. 2024 · 2024
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Scicode: A research coding benchmark curated by scientists
Minyang Tian, Luyu Gao, Shizhuo Dylan Zhang, Xinan Chen, Cunwei Fan, Xuefei Guo, Roland Haas, Pan Ji, Kittithat Krongchon, Yao Li, et al. 2024 · 2024
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Self-driving laboratories for chemistry and materials science
Gary Tom, Stefan P Schmid, Sterling G Baird, Yang Cao, Kourosh Darvish, Han Hao, Stanley Lo, Sergio Pablo-García, Ella M Rajaonson, Marta Skreta, et al. 2024 · 2024
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Bridging text and molecule: A survey on multimodal frameworks for molecule
Yi Xiao, Xiangxin Zhou, Qiang Liu, and Liang Wang. 2024 · 2024
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Hallucination is inevitable: An innate limitation of large language models
Ziwei Xu, Sanjay Jain, and Mohan Kankanhalli. 2024 · 2024
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Deco: Decoupling token compression from semantic abstraction in multimodal large language models
Linli Yao, Lei Li, Shuhuai Ren, Lean Wang, Yuanxin Liu, Xu Sun, and Lu Hou. 2024 · 2024
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Yanpeng Ye, Jie Ren, Shaozhou Wang, Yuwei Wan, Imran Razzak, Tong Xie, and Wenjie Zhang. 2024 · 2024
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Botao Yu, Frazier N Baker, Ziqi Chen, Xia Ning, and Huan Sun. 2024 · 2024
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Artem Zholus, Maksim Kuznetsov, Roman Schutski, Rim Shayakhmetov, Daniil Polykovskiy, Sarath Chandar, and Alex Zhavoronkov. 2024 · 2024
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Lawgpt: A chinese legal knowledge-enhanced large language model
Zhi Zhou, Jiang-Xin Shi, Peng-Xiao Song, Xiao-Wen Yang, Yi-Xuan Jin, Lan-Zhe Guo, and Yu-Feng Li. 2024 · 2024
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