Fetching the paper…
Reading the bibliography…
We present a PaperRobot who performs as an automatic research assistant by (1) conducting deep understanding of a large collection of human-written papers in a target domain and constructing comprehensive background knowledge graphs (KGs); (2) creating new ideas by predicting links from the background KGs, by combining graph attention and contextual text attention; (3) incrementally writing some key elements of a new paper based on memory-attention networks: from the input title along with predicted related entities to generate a paper abstract, from the abstract to generate conclusion and future work, and finally from future work to generate a title for a follow-on paper.
BLEU: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002
Earlier work this paper cites.
ROUGE: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
Earlier work this paper cites.
A study of translation edit rate with targeted human annotation
Matthew Snover, Bonnie Dorr, Richard Schwartz, Linnea Micciulla, and John Makhoul. 2006 · 2006
Earlier work this paper cites.
Avoiding repetition in generated text
Mary Ellen Foster and Michael White. 2007 · 2007
Earlier work this paper cites.
Accelerated gradient methods for stochastic optimization and online learning
Chonghai Hu, Weike Pan, and James T. Kwok. 2009 · 2009
Earlier work this paper cites.
A three-way model for collective learning on multi-relational data
Maximilian Nickel, Volker Tresp, and Hans-Peter Kriegel. 2011 · 2011
Earlier work this paper cites.
Snail transcription factor negatively regulates maspin tumor suppressor in human prostate cancer cells
Corey L. Neal, Veronica Henderson, Bethany N. Smith, Danielle McKeithen, Tisheeka Graham, Baohan T. Vo, and Valerie A. Odero-Marah. 2012 · 2012
Earlier work this paper cites.
Role of maspin in cancer
Rossana Berardi, Francesca Morgese, Azzurra Onofri, Paola Mazzanti, Mirco Pistelli, Zelmira Ballatore, Agnese Savini, Mariagrazia De Lisa, Miriam Caramanti, Silvia Rinaldi, et al. 2013 · 2013
Earlier work this paper cites.
Translating embeddings for modeling multi-relational data
Antoine Bordes, Nicolas Usunier, Alberto Garcia-Duran, Jason Weston, and Oksana Yakhnenko. 2013 · 2013
Earlier work this paper cites.
Generating natural language from linked data: Unsupervised template extraction
Daniel Duma and Ewan Klein. 2013 · 2013
Earlier work this paper cites.
A global model for concept-to-text generation
Ioannis Konstas and Mirella Lapata. 2013 · 2013
Earlier work this paper cites.
Generating natural-language video descriptions using text-mined knowledge
Niveda Krishnamoorthy, Girish Malkarnenkar, Raymond J Mooney, Kate Saenko, and Sergio Guadarrama. 2013 · 2013
Earlier work this paper cites.
The acl anthology network corpus
Dragomir R. Radev, Pradeep Muthukrishnan, Vahed Qazvinian, and Amjad Abu-Jbara. 2013 · 2013
Earlier work this paper cites.
PubTator: a web-based text mining tool for assisting biocuration
Chih-Hsuan Wei, Hung-Yu Kao, and Zhiyong Lu. 2013 · 2013
Earlier work this paper cites.
Learning phrase representations using rnn encoder-decoder for statistical machine translation
Kyunghyun Cho, Bart Van Merriënboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio. 2014 · 2014
Earlier work this paper cites.
Meteor universal: Language specific translation evaluation for any target language
Michael Denkowski and Alon Lavie. 2014 · 2014
Earlier work this paper cites.
Why academics stink at writing
Steven Pinker. 2014 · 2014
Earlier work this paper cites.
Scientists may be reaching a peak in reading habits
Richard Van Noorden. 2014 · 2014
Earlier work this paper cites.
Knowledge graph embedding by translating on hyperplanes
Zhen Wang, Jianwen Zhang, Jianlin Feng, and Zheng Chen. 2014 · 2014
Earlier work this paper cites.
Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2015 · 2015
Cited alongside, same era.
Tradition and innovation in scientists’ research strategies
Jacob G. Foster, Andrey Rzhetsky, and James A. Evans. 2015 · 2015
Cited alongside, same era.
Framewise phoneme classification with bidirectional lstm and other neural network architectures
Alex Graves and Jürgen Schmidhuber. 2005 · 2015
Cited alongside, same era.
Learning entity and relation embeddings for knowledge graph completion
Yankai Lin, Zhiyuan Liu, Maosong Sun, Yang Liu, and Xuan Zhu. 2015 · 2015
Cited alongside, same era.
The Ubuntu dialogue corpus: A large dataset for research in unstructured multi-turn dialogue systems
Ryan Lowe, Nissan Pow, Iulian Serban, and Joelle Pineau. 2015 · 2015
Cited alongside, same era.
End-to-end memory networks
Neural text generation: A practical guide
Ziang Xie. 2017 · 2017
Later among the works it cites.
Knowledge graph representation with jointly structural and textual encoding
Jiacheng Xu, Kan Chen, Xipeng Qiu, and Xuanjing Huang. 2017 · 2017
Later among the works it cites.
Hierarchical neural story generation
Angela Fan, Mike Lewis, and Yann Dauphin. 2018 · 2018
Later among the works it cites.
Guided neural language generation for abstractive summarization using Abstract Meaning Representation
Hardy Hardy and Andreas Vlachos. 2018 · 2018
Later among the works it cites.
Learning to generate Wikipedia summaries for underserved languages from Wikidata
Lucie-Aimée Kaffee, Hady Elsahar, Pavlos Vougiouklis, Christophe Gravier, Frederique Laforest, Jonathon Hare, and Elena Simperl. 2018 · 2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Sainbayar Sukhbaatar, Jason Weston, Rob Fergus, et al. 2015 · 2015
Cited alongside, same era.
Generation from abstract meaning representation using tree transducers
Jeffrey Flanigan, Chris Dyer, Noah A. Smith, and Jaime Carbonell. 2016 · 2016
Cited alongside, same era.
Incorporating copying mechanism in sequence-to-sequence learning
Jiatao Gu, Zhengdong Lu, Hang Li, and Victor O.K. Li. 2016 · 2016
Cited alongside, same era.
Neural text generation from structured data with application to the biography domain
Rémi Lebret, David Grangier, and Michael Auli. 2016 · 2016
Cited alongside, same era.
A persona-based neural conversation model
Jiwei Li, Michel Galley, Chris Brockett, Georgios Spithourakis, Jianfeng Gao, and Bill Dolan. 2016 · 2016
Cited alongside, same era.
How not to evaluate your dialogue system: An empirical study of unsupervised evaluation metrics for dialogue response generation
Chia-Wei Liu, Ryan Lowe, Iulian Serban, Mike Noseworthy, Laurent Charlin, and Joelle Pineau. 2016 · 2016
Cited alongside, same era.
Generating English from Abstract Meaning Representations
Nima Pourdamghani, Kevin Knight, and Ulf Hermjakob. 2016 · 2016
Cited alongside, same era.
Table-to-text generation by structure-aware seq2seq learning
Tianyu Liu, Kexiang Wang, Lei Sha, Baobao Chang, and Zhifang Sui. 2018 · 2018
Later among the works it cites.
Entity-aware image caption generation
Di Lu, Spencer Whitehead, Lifu Huang, Heng Ji, and Shih-Fu Chang. 2018 · 2018
Later among the works it cites.
Multi-task identification of entities, relations, and coreference for scientific knowledge graph construction
Yi Luan, Luheng He, Mari Ostendorf, and Hannaneh Hajishirzi. 2018 · 2018
Later among the works it cites.
Mem2seq: Effectively incorporating knowledge bases into end-to-end task-oriented dialog systems
Andrea Madotto, Chien-Sheng Wu, and Pascale Fung. 2018 · 2018
Later among the works it cites.
Operation-guided neural networks for high fidelity data-to-text generation
Feng Nie, Jinpeng Wang, Jin-Ge Yao, Rong Pan, and Chin-Yew Lin. 2018 · 2018
Later among the works it cites.
Order-planning neural text generation from structured data
Lei Sha, Lili Mou, Tianyu Liu, Pascal Poupart, Sujian Li, Baobao Chang, and Zhifang Sui. 2018 · 2018
Later among the works it cites.
GTR-LSTM: A triple encoder for sentence generation from RDF data
Bayu Distiawan Trisedya, Jianzhong Qi, Rui Zhang, and Wei Wang. 2018 · 2018
Later among the works it cites.
When science journalism meets artificial intelligence: An interactive demonstration
Raghuram Vadapalli, Bakhtiyar Syed, Nishant Prabhu, Balaji Vasan Srinivasan, and Vasudeva Varma. 2018 · 2018
Later among the works it cites.
Graph attention networks
Petar Veličković, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Liò, and Yoshua Bengio. 2018 · 2018
Later among the works it cites.
Incorporating background knowledge into video description generation
Spencer Whitehead, Heng Ji, Mohit Bansal, Shih-Fu Chang, and Clare Voss. 2018 · 2018
Later among the works it cites.
Learning neural templates for text generation
Sam Wiseman, Stuart Shieber, and Alexander Rush. 2018 · 2018
Later among the works it cites.
Image captioning and visual question answering based on attributes and external knowledge
Qi Wu, Chunhua Shen, Peng Wang, Anthony Dick, and Anton van den Hengel. 2018 · 2018
Later among the works it cites.
SQL-to-text generation with graph-to-sequence model
Kun Xu, Lingfei Wu, Zhiguo Wang, Yansong Feng, and Vadim Sheinin. 2018 · 2018
Later among the works it cites.