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The volume of scientific literature is growing exponentially, leading to underutilized discoveries, duplicated efforts, and limited cross-disciplinary collaboration.
A question-answering framework for automated abstract screening using large language models
Opeoluwa Akinseloyin, Xiaorui Jiang, and Vasile Palade. 2024 · 1952
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Bleu: a method for automatic evaluation of machine translation. In Proceedings of the 40th annual meeting of the Association for Computational Linguistics . 311–318
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002
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Dense Passage Retrieval for Open-Domain Question Answering
Vladimir Karpukhin, Barlas Oğuz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen tau Yih. 2020 · 2004
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APD: The antimicrobial peptide database
Zhe Wang and Guangshun Wang. 2004 · 2004
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Contrastive Representation Learning: A Framework and Review
Phuc H. Le-Khac, Graham Healy, and Alan F. Smeaton. 2020 · 2010
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Efficient Estimation of Word Representations in Vector Space
Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. 2013 · 2013
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Scientists may be reaching a peak in reading habits
Richard Van Noorden. 2014 · 2014
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Character-based parsing with convolutional neural network. In Twenty-Fourth International Joint Conference on Artificial Intelligence
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Semantics, Analytics, Visualization. Enhancing Scholarly Data
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Scientific literature: Information overload
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You only look once: Unified, real-time object detection. In IEEE Conference on Computer Vision and Pattern Recognition . 779–788
Joseph Redmon, Santosh Divvala, Ross Girshick, and Ali Farhadi. 2016 · 2016
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MSL: Facilitating automatic and physical analysis of published scientific literature in PDF format
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Crowdsourcing Multiple Choice Science Questions
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Science of science
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SciTaiL: A textual entailment dataset from science question answering. In AAAI Conference on Artificial Intelligence , Vol. 32
Tushar Khot, Ashish Sabharwal, and Peter Clark. 2018 · 2018
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Parsl: Pervasive Parallel Programming in Python. In ACM International Symposium on High-Performance Parallel and Distributed Computing
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Learning Representations by Maximizing Mutual Information Across Views
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BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies . 4171–4186
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BioBERT: a pre-trained biomedical language representation model for biomedical text mining
Jinhyuk Lee, Wonjin Yoon, Sungdong Kim, Donghyeon Kim, Sunkyu Kim, Chan Ho So, and Jaewoo Kang. 2019 · 2019
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Molecular Transformer: A Model for Uncertainty-Calibrated Chemical Reaction Prediction
Philippe Schwaller, Teodoro Laino, Théophile Gaudin, Peter Bolgar, Christopher A. Hunter, Costas Bekas, and Alpha A. Lee. 2019 · 2019
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Unsupervised word embeddings capture latent knowledge from materials science literature
Vahe Tshitoyan, John Dagdelen, Leigh Weston, Alexander Dunn, Ziqin Rong, Olga Kononova, Kristin A. Persson, Gerbrand Ceder, and Anubhav Jain. 2019 · 2019
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The Pile: An 800GB Dataset of Diverse Text for Language Modeling
Leo Gao, Stella Biderman, Sid Black, Laurence Golding, Travis Hoppe, Charles Foster, Jason Phang, Horace He, Anish Thite, Noa Nabeshima, Shawn Presser, and Connor Leahy. 2020 · 2020
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ColBERT: Efficient and effective passage search via contextualized late interaction over BERT. In 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval . 39–48
Omar Khattab and Matei Zaharia. 2020 · 2020
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Retrieval-augmented generation for knowledge-intensive NLP tasks. In 34th International Conference on Neural Information Processing Systems (Vancouver, BC, Canada) (NIPS’20) . Curran Associates Inc., Red Hook, NY, USA, Article 793, 16 pages
Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, Sebastian Riedel, and Douwe Kiela. 2020 · 2020
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LayoutLM: Pre-training of text and layout for document image understanding. In 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining . 1192–1200
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Slowed canonical progress in large fields of science
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SimCSE: Simple Contrastive Learning of Sentence Embeddings. In Conference on Empirical Methods in Natural Language Processing , Marie-Francine Moens, Xuanjing Huang, Lucia Specia, and Scott Wen-tau Yih (Eds.). Association for Computational Linguistics, Online and Punta Cana, Dominican Republic, 6894–6910
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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. 2021a · 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. 2021b · 2021
Cited alongside, same era.
New directions in science emerge from disconnection and discord
Yiling Lin, James A. Evans, and Lingfei Wu. 2022 · 2021
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Pretrained Transformers as Universal Computation Engines
Kevin Lu, Aditya Grover, Pieter Abbeel, and Igor Mordatch. 2021 · 2021
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Global citation inequality is on the rise
Mathias Wullum Nielsen and Jens Peter Andersen. 2021 · 2021
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DBAASP v3: Database of antimicrobial/cytotoxic activity and structure of peptides as a resource for development of new therapeutics
Malak Pirtskhalava, Anthony A Amstrong, Maia Grigolava, Mindia Chubinidze, Evgenia Alimbarashvili, Boris Vishnepolsky, Andrei Gabrielian, Alex Rosenthal, Darrell E Hurt, and Michael Tartakovsky. 2021 · 2021
Albert Q. Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, Lélio Renard Lavaud, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Thibaut Lavril, Thomas Wang, Timothée Lacroix, and William El Sayed. 2023 · 2023
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PaperQA: Retrieval-augmented generative agent for scientific research
Jakub Lála, Odhran O’Donoghue, Aleksandar Shtedritski, Sam Cox, Samuel G Rodriques, and Andrew D White. 2023 · 2023
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AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation
Qingyun Wu, Gagan Bansal, Jieyu Zhang, Yiran Wu, Beibin Li, Erkang Zhu, Li Jiang, Xiaoyun Zhang, Shaokun Zhang, Jiale Liu, Ahmed Hassan Awadallah, Ryen W White, Doug Burger, and Chi Wang. 2023 · 2023
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Retrieving Multimodal Information for Augmented Generation: A Survey
Ruochen Zhao, Hailin Chen, Weishi Wang, Fangkai Jiao, Xuan Long Do, Chengwei Qin, Bosheng Ding, Xiaobao Guo, Minzhi Li, Xingxuan Li, and Shafiq Joty. 2023 · 2023
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
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UniProt: The universal protein knowledgebase in 2021
UniProt Consortium. 2021 · 2021
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FILIP: Fine-grained Interactive Language-Image Pre-Training
Lewei Yao, Runhui Huang, Lu Hou, Guansong Lu, Minzhe Niu, Hang Xu, Xiaodan Liang, Zhenguo Li, Xin Jiang, and Chunjing Xu. 2021 · 2021
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Stanford CRFM Introduces PubMedGPT 2.7B
E. Bolton, D. Hall, M. Yasunaga, T. Lee, C. Manning, and P. Liang. 2022 · 2022
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MuRAG: Multimodal Retrieval-Augmented Generator for Open Question Answering over Images and Text
Wenhu Chen, Hexiang Hu, Xi Chen, Pat Verga, and William W. Cohen. 2022 · 2022
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LoRA: Low-Rank Adaptation of Large Language Models. In International Conference on Learning Representations
Edward J Hu, yelong shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2022 · 2022
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OCR-free document understanding transformer. In European Conference on Computer Vision . Springer, 498–517
Geewook Kim, Teakgyu Hong, Moonbin Yim, JeongYeon Nam, Jinyoung Park, Jinyeong Yim, Wonseok Hwang, Sangdoo Yun, Dongyoon Han, and Seunghyun Park. 2022 · 2022
Cited alongside, same era.
Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning
Haokun Liu, Derek Tam, Mohammed Muqeeth, Jay Mohta, Tenghao Huang, Mohit Bansal, and Colin Raffel. 2022 · 2022
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Marie and BERT–A Knowledge Graph Embedding Based Question Answering System for Chemistry
Xiaochi Zhou, Shaocong Zhang, Mehal Agarwal, Jethro Akroyd, Sebastian Mosbach, and Markus Kraft. 2023 · 2023
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PDFMiner
2024 · 2024
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PyMuPDF Documentation
2024 · 2024
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PyPDF Documentation
2024 · 2024
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Golden-Retriever: High-Fidelity Agentic Retrieval Augmented Generation for Industrial Knowledge Base
Zhiyu An, Xianzhong Ding, Yen-Chun Fu, Cheng-Chung Chu, Yan Li, and Wan Du. 2024 · 2024
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Machine-assisted social psychology hypothesis generation
Sachin Banker, Promothesh Chatterjee, Himanshu Mishra, and Arul Mishra. 2024 · 2024
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https://github.com/braceal/parsl_object_registry
Alexander Brace and J. Gregory Pauloski. 2023 · 2024
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Kexin Chen, Junyou Li, Kunyi Wang, Yuyang Du, Jiahui Yu, Jiamin Lu, Lanqing Li, Jiezhong Qiu, Jianzhang Pan, Yi Huang, Qun Fang, Pheng Ann Heng, and Guangyong Chen. 2024 · 2024
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Science and Engineering Indicators 2024: The State of U.S. Science and Engineering
Steven Deitz and Christina Freyman. 2024 · 2024
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Matthijs Douze, Alexandr Guzhva, Chengqi Deng, Jeff Johnson, Gergely Szilvasy, Pierre-Emmanuel Mazaré, Maria Lomeli, Lucas Hosseini, and Hervé Jégou. 2024 · 2024
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From Local to Global: A Graph RAG Approach to Query-Focused Summarization
Darren Edge, Ha Trinh, Newman Cheng, Joshua Bradley, Alex Chao, Apurva Mody, Steven Truitt, and Jonathan Larson. 2024 · 2024
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TinyAgent: Function Calling at the Edge
Lutfi Eren Erdogan, Nicholas Lee, Siddharth Jha, Sehoon Kim, Ryan Tabrizi, Suhong Moon, Coleman Hooper, Gopala Anumanchipalli, Kurt Keutzer, and Amir Gholami. 2024 · 2024
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Leveraging Long-Context Large Language Models for Multi-Document Understanding and Summarization in Enterprise Applications
Aditi Godbole, Jabin Geevarghese George, and Smita Shandilya. 2024 · 2024
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Robust Multi Model RAG Pipeline For Documents Containing Text, Table & Images. In 3rd International Conference on Applied Artificial Intelligence and Computing . 993–999
Pankaj Joshi, Aditya Gupta, Pankaj Kumar, and Manas Sisodia. 2024 · 2024
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KRAGEN: a knowledge graph-enhanced RAG framework for biomedical problem solving using large language models
Nicholas Matsumoto, Jay Moran, Hyunjun Choi, Miguel E Hernandez, Mythreye Venkatesan, Paul Wang, and Jason H Moore. 2024 · 2024
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SFR-Embedding-Mistral:Enhance Text Retrieval with Transfer Learning
Rui Meng, Ye Liu, Shafiq Rayhan Joty, Caiming Xiong, Yingbo Zhou, and Semih Yavuz. 2024 · 2024
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G-RAG: Knowledge Expansion in Material Science
Radeen Mostafa, Mirza Nihal Baig, Mashaekh Tausif Ehsan, and Jakir Hasan. 2024 · 2024
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Texify: Tool for Converting Text to LaTeX
Vik Paruchuri. [n. d.] · 2024
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Agentic Retrieval-Augmented Generation for Time Series Analysis
Chidaksh Ravuru, Sagar Srinivas Sakhinana, and Venkataramana Runkana. 2024 · 2024
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Dolma: An Open Corpus of Three Trillion Tokens for Language Model Pretraining Research
Luca Soldaini, Rodney Kinney, Akshita Bhagia, Dustin Schwenk, David Atkinson, Russell Authur, Ben Bogin, Khyathi Chandu, Jennifer Dumas, Yanai Elazar, Valentin Hofmann, Ananya Harsh Jha, Sachin Kumar, Li Lucy, Xinxi Lyu, Nathan Lambert, Ian Magnusson, Jacob Morrison, Niklas Muennighoff, Aakanksha Naik, Crystal Nam, Matthew E. Peters, Abhilasha Ravichander, Kyle Richardson, Zejiang Shen, Emma Strubell, Nishant Subramani, Oyvind Tafjord, Pete Walsh, Luke Zettlemoyer, Noah A. Smith, Hannaneh Hajishirzi, Iz Beltagy, Dirk Groeneveld, Jesse Dodge, and Kyle Lo. 2024 · 2024
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November 2024 TOP500
Top500. 2024 · 2024
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High Performance Binding Affinity Prediction with a Transformer-Based Surrogate Model. In 2024 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW) . 571–580
Archit Vasan, Ozan Gokdemir, Alexander Brace, Arvind Ramanathan, Thomas Brettin, Rick Stevens, and Venkatram Vishwanath. 2024 · 2024
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BioRAG: A RAG-LLM Framework for Biological Question Reasoning
Chengrui Wang, Qingqing Long, Meng Xiao, Xunxin Cai, Chengjun Wu, Zhen Meng, Xuezhi Wang, and Yuanchun Zhou. 2024 · 2024
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