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Arvind Neelakantan
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2020 – today
- 2022
- [i18]Arvind Neelakantan, Tao Xu, Raul Puri, Alec Radford, Jesse Michael Han, Jerry Tworek, Qiming Yuan, Nikolas Tezak, Jong Wook Kim, Chris Hallacy, Johannes Heidecke, Pranav Shyam, Boris Power, Tyna Eloundou Nekoul, Girish Sastry, Gretchen Krueger, David Schnurr, Felipe Petroski Such, Kenny Hsu, Madeleine Thompson, Tabarak Khan, Toki Sherbakov, Joanne Jang, Peter Welinder, Lilian Weng:
Text and Code Embeddings by Contrastive Pre-Training. CoRR abs/2201.10005 (2022) - 2021
- [i17]Jesse Michael Han, Igor Babuschkin, Harrison Edwards, Arvind Neelakantan, Tao Xu, Stanislas Polu, Alex Ray, Pranav Shyam, Aditya Ramesh, Alec Radford, Ilya Sutskever:
Unsupervised Neural Machine Translation with Generative Language Models Only. CoRR abs/2110.05448 (2021) - 2020
- [c15]Prasanna Parthasarathi, Sharan Narang, Arvind Neelakantan:
On Task-Level Dialogue Composition of Generative Transformer Model. Insights 2020: 41-47 - [c14]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, Dario Amodei:
Language Models are Few-Shot Learners. NeurIPS 2020 - [i16]Hugh Zhang, Daniel Duckworth, Daphne Ippolito, Arvind Neelakantan:
Trading Off Diversity and Quality in Natural Language Generation. CoRR abs/2004.10450 (2020) - [i15]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, Dario Amodei:
Language Models are Few-Shot Learners. CoRR abs/2005.14165 (2020) - [i14]Prasanna Parthasarathi, Arvind Neelakantan, Sharan Narang:
On Task-Level Dialogue Composition of Generative Transformer Model. CoRR abs/2010.04826 (2020)
2010 – 2019
- 2019
- [c13]Bill Byrne, Karthik Krishnamoorthi, Chinnadhurai Sankar, Arvind Neelakantan, Ben Goodrich, Daniel Duckworth, Semih Yavuz, Amit Dubey, Kyu-Young Kim, Andy Cedilnik:
Taskmaster-1: Toward a Realistic and Diverse Dialog Dataset. EMNLP/IJCNLP (1) 2019: 4515-4524 - [i13]Daniel Duckworth, Arvind Neelakantan, Ben Goodrich, Lukasz Kaiser, Samy Bengio:
Parallel Scheduled Sampling. CoRR abs/1906.04331 (2019) - [i12]Bill Byrne, Karthik Krishnamoorthi, Chinnadhurai Sankar, Arvind Neelakantan, Daniel Duckworth, Semih Yavuz, Ben Goodrich, Amit Dubey, Andy Cedilnik, Kyu-Young Kim:
Taskmaster-1: Toward a Realistic and Diverse Dialog Dataset. CoRR abs/1909.05358 (2019) - [i11]Arvind Neelakantan, Semih Yavuz, Sharan Narang, Vishaal Prasad, Ben Goodrich, Daniel Duckworth, Chinnadhurai Sankar, Xifeng Yan:
Neural Assistant: Joint Action Prediction, Response Generation, and Latent Knowledge Reasoning. CoRR abs/1910.14613 (2019) - 2018
- [i10]Aurko Roy, Ashish Vaswani, Arvind Neelakantan, Niki Parmar:
Theory and Experiments on Vector Quantized Autoencoders. CoRR abs/1805.11063 (2018) - 2017
- [c12]Trapit Bansal, Arvind Neelakantan, Andrew McCallum:
RelNet: End-to-end Modeling of Entities & Relations. AKBC@NIPS 2017 - [c11]Rajarshi Das, Arvind Neelakantan, David Belanger, Andrew McCallum:
Chains of Reasoning over Entities, Relations, and Text using Recurrent Neural Networks. EACL (1) 2017: 132-141 - [c10]Patrick Verga, Arvind Neelakantan, Andrew McCallum:
Generalizing to Unseen Entities and Entity Pairs with Row-less Universal Schema. EACL (1) 2017: 613-622 - [c9]Arvind Neelakantan, Quoc V. Le, Martín Abadi, Andrew McCallum, Dario Amodei:
Learning a Natural Language Interface with Neural Programmer. ICLR (Poster) 2017 - [i9]Trapit Bansal, Arvind Neelakantan, Andrew McCallum:
RelNet: End-to-end Modeling of Entities & Relations. CoRR abs/1706.07179 (2017) - 2016
- [j1]Kathy McKeown, Hal Daumé III, Snigdha Chaturvedi, John Paparrizos
, Kapil Thadani, Pablo Barrio, Or Biran, Suvarna Bothe, Michael Collins, Kenneth R. Fleischmann, Luis Gravano, Rahul Jha, Ben King, Kevin McInerney, Taesun Moon, Arvind Neelakantan, Diarmuid Ó Séaghdha, Dragomir R. Radev, Thomas Clay Templeton, Simone Teufel:
Predicting the impact of scientific concepts using full-text features. J. Assoc. Inf. Sci. Technol. 67(11): 2684-2696 (2016) - [c8]Rajarshi Das, Arvind Neelakantan, David Belanger, Andrew McCallum:
Incorporating Selectional Preferences in Multi-hop Relation Extraction. AKBC@NAACL-HLT 2016: 18-23 - [c7]Arvind Neelakantan, Quoc V. Le, Ilya Sutskever:
Neural Programmer: Inducing Latent Programs with Gradient Descent. ICLR (Poster) 2016 - [i8]Patrick Verga, Arvind Neelakantan, Andrew McCallum:
Generalizing to Unseen Entities and Entity Pairs with Row-less Universal Schema. CoRR abs/1606.05804 (2016) - [i7]Rajarshi Das, Arvind Neelakantan, David Belanger, Andrew McCallum:
Chains of Reasoning over Entities, Relations, and Text using Recurrent Neural Networks. CoRR abs/1607.01426 (2016) - [i6]Arvind Neelakantan, Quoc V. Le, Martín Abadi, Andrew McCallum, Dario Amodei:
Learning a Natural Language Interface with Neural Programmer. CoRR abs/1611.08945 (2016) - 2015
- [c6]Arvind Neelakantan, Benjamin Roth, Andrew McCallum:
Compositional Vector Space Models for Knowledge Base Inference. AAAI Spring Symposia 2015 - [c5]Arvind Neelakantan, Benjamin Roth, Andrew McCallum:
Compositional Vector Space Models for Knowledge Base Completion. ACL (1) 2015: 156-166 - [c4]Arvind Neelakantan, Ming-Wei Chang:
Inferring Missing Entity Type Instances for Knowledge Base Completion: New Dataset and Methods. HLT-NAACL 2015: 515-525 - [i5]Arvind Neelakantan, Michael Collins:
Learning Dictionaries for Named Entity Recognition using Minimal Supervision. CoRR abs/1504.06650 (2015) - [i4]Arvind Neelakantan, Jeevan Shankar, Alexandre Passos, Andrew McCallum:
Efficient Non-parametric Estimation of Multiple Embeddings per Word in Vector Space. CoRR abs/1504.06654 (2015) - [i3]Arvind Neelakantan, Ming-Wei Chang:
Inferring Missing Entity Type Instances for Knowledge Base Completion: New Dataset and Methods. CoRR abs/1504.06658 (2015) - [i2]Arvind Neelakantan, Benjamin Roth, Andrew McCallum:
Compositional Vector Space Models for Knowledge Base Completion. CoRR abs/1504.06662 (2015) - [i1]Arvind Neelakantan, Luke Vilnis, Quoc V. Le, Ilya Sutskever, Lukasz Kaiser, Karol Kurach, James Martens:
Adding Gradient Noise Improves Learning for Very Deep Networks. CoRR abs/1511.06807 (2015) - 2014
- [c3]Arvind Neelakantan, Michael Collins:
Learning Dictionaries for Named Entity Recognition using Minimal Supervision. EACL 2014: 452-461 - [c2]Arvind Neelakantan, Jeevan Shankar, Alexandre Passos, Andrew McCallum:
Efficient Non-parametric Estimation of Multiple Embeddings per Word in Vector Space. EMNLP 2014: 1059-1069 - 2012
- [c1]Rohit Prasad, Rohit Kumar, Sankaranarayanan Ananthakrishnan, Wei Chen, Sanjika Hewavitharana, Matthew E. Roy, Fred Choi, Aaron Challenner, Enoch Kan, Arvind Neelakantan, Prem Natarajan:
Active error detection and resolution for speech-to-speech translation. IWSLT 2012: 150-157
Coauthor Index
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