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Jonathan Berant
Jonathan Berant
Associate Professor, Tel-Aviv University, Visiting Faculty Researcher, Google DeepMInd
Zweryfikowany adres z cs.tau.ac.il - Strona główna
Tytuł
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Cytowane przez
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Semantic parsing on freebase from question-answer pairs
J Berant, A Chou, R Frostig, P Liang
Proceedings of the 2013 conference on empirical methods in natural language …, 2013
23722013
CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledge
A Talmor, J Herzig, N Lourie, J Berant
NAACL 2019, 2018
16282018
Beyond the imitation game: Quantifying and extrapolating the capabilities of language models
A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ...
arXiv preprint arXiv:2206.04615, 2022
13932022
Semantic parsing via paraphrasing
J Berant, P Liang
Proceedings of the 52nd Annual Meeting of the Association for Computational …, 2014
6992014
Transformer feed-forward layers are key-value memories
M Geva, R Schuster, J Berant, O Levy
EMNLP 2021, 0
692*
The web as a knowledge-base for answering complex questions
A Talmor, J Berant
NAACL 2018, 2018
6612018
Learning To Retrieve Prompts for In-Context Learning
O Rubin, J Herzig, J Berant
NAACL 2022, 2021
6322021
Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies
M Geva, D Khashabi, E Segal, T Khot, D Roth, J Berant
TACL 2021, 2021
6112021
Evaluating models' local decision boundaries via contrast sets
M Gardner, Y Artzi, V Basmova, J Berant, B Bogin, S Chen, P Dasigi, ...
arXiv preprint arXiv:2004.02709, 2020
4932020
Neural symbolic machines: Learning semantic parsers on freebase with weak supervision
C Liang, J Berant, Q Le, KD Forbus, N Lao
ACL, 2016
4782016
Building a semantic parser overnight
Y Wang, J Berant, P Liang
Proceedings of the 53rd Annual Meeting of the Association for Computational …, 2015
4102015
Are we modeling the task or the annotator? an investigation of annotator bias in natural language understanding datasets
M Geva, Y Goldberg, J Berant
EMNLP 2019, 2019
3772019
Diagonal State Spaces are as Effective as Structured State Spaces
A Gupta, A Gu, J Berant
Neurips 2022, 2022
3232022
Modeling biological processes for reading comprehension
J Berant, V Srikumar, PC Chen, A Vander Linden, B Harding, B Huang, ...
Proceedings of the 2014 conference on empirical methods in natural language …, 2014
2732014
oLMpics-on what language model pre-training captures
A Talmor, Y Elazar, Y Goldberg, J Berant
Transactions of the Association for Computational Linguistics 8, 743-758, 2020
2472020
Injecting Numerical Reasoning Skills into Language Models
M Geva, A Gupta, J Berant
ACL 2020, 2020
2372020
Representing Schema Structure with Graph Neural Networks for Text-to-SQL Parsing
B Bogin, M Gardner, J Berant
ACL, 2019
2212019
Coarse-to-fine question answering for long documents
E Choi, D Hewlett, J Uszkoreit, I Polosukhin, A Lacoste, J Berant
Proceedings of the 55th Annual Meeting of the Association for Computational …, 2017
218*2017
MultiQA: An Empirical Investigation of Generalization and Transfer in Reading Comprehension
A Talmor, J Berant
ACL, 2019
2122019
Text segmentation as a supervised learning task
O Koshorek, A Cohen, N Mor, M Rotman, J Berant
NAACL 2018, 2018
1992018
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