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Literature reviews are an essential component of scientific research, but they remain time-intensive and challenging to write, especially due to the recent influx of research papers.
Building applied natural language generation systems
Ehud Reiter and Robert Dale · 1997
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Lexrank: Graph-based lexical centrality as salience in text summarization
Günes Erkan and Dragomir R Radev · 2004
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ROUGE: A package for automatic evaluation of summaries
Chin-Yew Lin · 2004
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Textrank: Bringing order into text
Rada Mihalcea and Paul Tarau · 2004
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Trainable sentence planning for complex information presentations in spoken dialog systems
Amanda Stent, Rashmi Prasad, and Marilyn Walker · 2004
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Language models are few-shot learners, 2020
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei · 2005
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Individual and domain adaptation in sentence planning for dialogue
Marilyn A Walker, Amanda Stent, François Mairesse, and Rashmi Prasad · 2007
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GROBID, February 2023
Patrice Lopez · 2012
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Mcnemar test
Peter A Lachenbruch · 2014
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Deep inside convolutional networks: Visualising image classification models and saliency maps
Karen Simonyan, Andrea Vedaldi, and Andrew Zisserman · 2014
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An overview of microsoft academic service (mas) and applications
Arnab Sinha, Zhihong Shen, Yang Song, Hao Ma, Darrin Eide, Bo-June Hsu, and Kuansan Wang · 2015
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Visualizing and understanding neural models in nlp
Jiwei Li, Xinlei Chen, Eduard Hovy, and Dan Jurafsky · 2016
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“why should i trust you?”: Explaining the predictions of any classifier
Marco Tulio Ribeiro, Sameer Singh, and Carlos Guestrin · 2016
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Interpretable explanations of black boxes by meaningful perturbation
Ruth C. Fong and Andrea Vedaldi · 2017
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Automatic differentiation in PyTorch
Adam Paszke, Sam Gross, Soumith Chintala, Gregory Chanan, Edward Yang, Zachary DeVito, Zeming Lin, Alban Desmaison, Luca Antiga, and Adam Lerer · 2017
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Get to the point: Summarization with pointer-generator networks
Abigail See, Peter J Liu, and Christopher D Manning · 2017
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Learning important features through propagating activation differences
Avanti Shrikumar, Peyton Greenside, and Anshul Kundaje · 2017
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Smoothgrad: Removing noise by adding noise
Daniel Smilkov, Nikhil Thorat, Been Kim, Fernanda Viégas, and Martin Wattenberg · 2017
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Axiomatic attribution for deep networks
Mukund Sundararajan, Ankur Taly, and Qiqi Yan · 2017
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Sanity checks for saliency maps
Julius Adebayo, Justin Gilmer, Michael Muelly, Ian Goodfellow, Moritz Hardt, and Been Kim · 2018
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
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End-to-end content and plan selection for data-to-text generation
Sebastian Gehrmann, Falcon Dai, Henry Elder, and Alexander Rush · 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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Interpretation of neural networks is fragile
Amirata Ghorbani, Abubakar Abid, and James Zou · 2019
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The (un) reliability of saliency methods
Pieter-Jan Kindermans, Sara Hooker, Julius Adebayo, Maximilian Alber, Kristof T. Schütt, Sven Dähne, Dumitru Erhan, and Been Kim · 2019
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Hierarchical transformers for multi-document summarization
Yang Liu and Mirella Lapata · 2019
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Data-to-text generation with content selection and planning
Ratish Puduppully, Li Dong, and Mirella Lapata · 2019
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Sentence-BERT: Sentence embeddings using Siamese BERT-networks
Nils Reimers and Iryna Gurevych · 2019
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Huggingface’s transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, et al · 2019
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TLDR: Extreme summarization of scientific documents
Isabel Cachola, Kyle Lo, Arman Cohan, and Daniel Weld · 2020
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Specter: Document-level representation learning using citation-informed transformers
Arman Cohan, Sergey Feldman, Iz Beltagy, Doug Downey, and Daniel S Weld · 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
Nougat: Neural optical understanding for academic documents, 2023
Lukas Blecher, Guillem Cucurull, Thomas Scialom, and Robert Stojnic · 2023
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Enabling large language models to generate text with citations
Tianyu Gao, Howard Yen, Jiatong Yu, and Danqi Chen · 2023
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Llama 2 is about as factually accurate as gpt-4 for summaries and is 30x cheaper, Aug 2023
M Waleed Kadous · 2023
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The semantic scholar open data platform
Rodney Kinney, Chloe Anastasiades, Russell Authur, Iz Beltagy, Jonathan Bragg, Alexandra Buraczynski, Isabel Cachola, Stefan Candra, Yoganand Chandrasekhar, Arman Cohan, et al · 2023
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A survey of large language models attribution, 2023
Dongfang Li, Zetian Sun, Xinshuo Hu, Zhenyu Liu, Ziyang Chen, Baotian Hu, Aiguo Wu, and Min Zhang · 2023
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
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S2ORC: The semantic scholar open research corpus
Kyle Lo, Lucy Lu Wang, Mark Neumann, Rodney Kinney, and Daniel Weld · 2020
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Multi-XScience: A large-scale dataset for extreme multi-document summarization of scientific articles
Yao Lu, Yue Dong, and Laurent Charlin · 2020
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On extractive and abstractive neural document summarization with transformer language models
Jonathan Pilault, Raymond Li, Sandeep Subramanian, and Chris Pal · 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
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unarXive: A Large Scholarly Data Set with Publications’ Full-Text, Annotated In-Text Citations, and Links to Metadata
Tarek Saier and Michael Färber · 2020
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SciXGen: A scientific paper dataset for context-aware text generation
Hong Chen, Hiroya Takamura, and Hideki Nakayama · 2021
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Capturing relations between scientific papers: An abstractive model for related work section generation
Xiuying Chen, Hind Alamro, Mingzhe Li, Shen Gao, Xiangliang Zhang, Dongyan Zhao, and Rui Yan · 2021
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G-eval: NLG evaluation using gpt-4 with better human alignment
Yang Liu, Dan Iter, Yichong Xu, Shuohang Wang, Ruochen Xu, and Chenguang Zhu · 2023
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Zero-shot listwise document reranking with a large language model
Xueguang Ma, Xinyu Zhang, Ronak Pradeep, and Jimmy Lin · 2023
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LoRaLay: A multilingual and multimodal dataset for long range and layout-aware summarization
Laura Nguyen, Thomas Scialom, Benjamin Piwowarski, and Jacopo Staiano · 2023
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GPT-4 technical report
OpenAI · 2023
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unarXive 2022: All arXiv Publications Pre-Processed for NLP, Including Structured Full-Text and Citation Network
Tarek Saier, Johan Krause, and Michael Färber · 2023
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Llm-planner: Few-shot grounded planning for embodied agents with large language models
Chan Hee Song, Jiaman Wu, Clayton Washington, Brian M Sadler, Wei-Lun Chao, and Yu Su · 2023
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Is ChatGPT good at search? investigating large language models as re-ranking agent
Weiwei Sun, Lingyong Yan, Xinyu Ma, Pengjie Ren, Dawei Yin, and Zhaochun Ren · 2023
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Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al · 2023
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Plan-and-solve prompting: Improving zero-shot chain-of-thought reasoning by large language models
Lei Wang, Wanyu Xu, Yihuai Lan, Zhiqiang Hu, Yunshi Lan, Roy Ka-Wei Lee, and Ee-Peng Lim · 2023
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Automatic evaluation of attribution by large language models, 2023
Xiang Yue, Boshi Wang, Ziru Chen, Kai Zhang, Yu Su, and Huan Sun · 2023
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Rank-without-gpt: Building gpt-independent listwise rerankers on open-source large language models
Xinyu Zhang, Sebastian Hofstätter, Patrick Lewis, Raphael Tang, and Jimmy Lin · 2023
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Hierarchical catalogue generation for literature review: A benchmark
Kun Zhu, Xiaocheng Feng, Xiachong Feng, Yingsheng Wu, and Bing Qin · 2023
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Litllm: A toolkit for scientific literature review
Shubham Agarwal, Issam H Laradji, Laurent Charlin, and Christopher Pal · 2024
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Contextcite: Attributing model generation to context, 2024
Benjamin Cohen-Wang, Harshay Shah, Kristian Georgiev, and Aleksander Madry · 2024
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On the attribution of confidence to large language models, 2024
Geoff Keeling and Winnie Street · 2024
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Language models can reduce asymmetry in information markets
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Introducing ai2 scholarqa, 2025
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A discourse-aware attention model for abstractive summarization of long documents
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