Sebastian Schuster

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Joakim NivreProfessor of Computational Linguistics, Uppsala University; Senior Researcher, RISEAdresse e-mail validée de lingfil.uu.se
Christopher D ManningProfessor of Computer Science and Linguistics, Stanford UniversityAdresse e-mail validée de stanford.edu
Filip GinterUniversity of TurkuAdresse e-mail validée de utu.fi
Marie-Catherine de MarneffeFNRS - UCLouvain - The Ohio State UniversityAdresse e-mail validée de uclouvain.be
Jan HajicProfessor of Computational Linguistics, Charles University, Prague, Czech RepublicAdresse e-mail validée de ufal.mff.cuni.cz
Daniel ZemanInstitute of Formal and Applied Linguistics, Faculty of Mathematics and Physics, Charles UniversityAdresse e-mail validée de ufal.mff.cuni.cz
Judith DegenAssociate professor, Stanford University (Linguistics)Adresse e-mail validée de stanford.edu
Ranjay KrishnaAssistant Professor, University of WashingtonAdresse e-mail validée de cs.washington.edu
Li Fei-FeiProfessor of Computer Science, Stanford UniversityAdresse e-mail validée de cs.stanford.edu
Angel ChangSimon Fraser UniversityAdresse e-mail validée de cs.stanford.edu
Tal LinzenNew York UniversityAdresse e-mail validée de nyu.edu
Rushin ShahGoogleAdresse e-mail validée de google.com
Sonal GuptaResearcher at GoogleAdresse e-mail validée de google.com
Mike LewisFacebook AI ResearchAdresse e-mail validée de fb.com
Roger LevyProfessor of Brain & Cognitive Sciences, MITAdresse e-mail validée de mit.edu
Jennifer HuHarvard UniversityAdresse e-mail validée de fas.harvard.edu
Jeffrey HeerUniversity of WashingtonAdresse e-mail validée de cs.washington.edu
Jason Chuang.Adresse e-mail validée de cs.stanford.edu
Sida I. WangFacebook AIAdresse e-mail validée de fb.com
Yuxing ChenMS in Symbolic Systems Program, Stanford UniversityAdresse e-mail validée de alumni.stanford.edu

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Sebastian Schuster

Lecturer in Computational Linguistics, University College London

Adresse e-mail validée de ucl.ac.uk - Page d'accueil

Natural Language Processing Artificial Intelligence Computational Linguistics Pragmatics


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
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	1181	2022
CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies D Zeman, and others Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw …, 2017	681	2017
Universal Dependencies v2: An Evergrowing Multilingual Treebank Collection J Nivre, MC de Marneffe, F Ginter, J Hajič, CD Manning, S Pyysalo, ... Proceedings of the Twelfth International Conference on Language Resources …, 2020	589	2020
Generating Semantically Precise Scene Graphs from Textual Descriptions for Improved Image Retrieval S Schuster, R Krishna, A Chang, L Fei-Fei, CD Manning Proceedings of the Fourth Workshop on Vision and Language, 70-80, 2015	375	2015
Enhanced English Universal Dependencies: An Improved Representation for Natural Language Understanding Tasks S Schuster, CD Manning Tenth International Conference on Language Resources and Evaluation (LREC 2016), 2016	343	2016
Cross-Lingual Transfer Learning for Multilingual Task Oriented Dialog S Schuster, S Gupta, R Shah, M Lewis Proceedings of the 2019 Conference of the North American Chapter of the …, 2019	313	2019
Universal Dependencies 2.0 J Nivre, et al. https://lindat.mff.cuni.cz/repository/xmlui/handle/11234/1-1983, 2017	266	2017
Human effort and machine learnability in computer aided translation S Green, SI Wang, J Chuang, J Heer, S Schuster, CD Manning Proceedings of the 2014 Conference on Empirical Methods in Natural Language …, 2014	90	2014
I know what you're probably going to say: Listener adaptation to variable use of uncertainty expressions S Schuster, J Degen Cognition 203, 2020	44	2020
Coloring the blank slate: Pre-training imparts a hierarchical inductive bias to sequence-to-sequence models A Mueller, R Frank, T Linzen, L Wang, S Schuster arXiv preprint arXiv:2203.09397, 2022	42	2022
Harnessing the linguistic signal to predict scalar inferences S Schuster, Y Chen, J Degen Proceedings of the 58th Annual Meeting of the Association for Computational …, 2020	39*	2020
HEATSTER: a database and web server for identification and classification of heat stress transcription factors in plants J Berz, S Simm, S Schuster, KD Scharf, E Schleiff, I Ebersberger Bioinformatics and biology insights 13, 1177932218821365, 2019	34	2019
Enhancing universal dependency treebanks: A case study J Nivre, P Marongiu, F Ginter, J Kanerva, S Montemagni, S Schuster, ... Proceedings of the Second Workshop on Universal Dependencies (UDW 2018), 102-107, 2018	30	2018
Entity tracking in language models N Kim, S Schuster arXiv preprint arXiv:2305.02363, 2023	28	2023
Sentences with Gapping: Parsing and Reconstructing Elided Predicates S Schuster, J Nivre, CD Manning Proceedings of the 2018 Conference of the North American Chapter of the …, 2018	27	2018
When a sentence does not introduce a discourse entity, Transformer-based models still sometimes refer to it S Schuster, T Linzen Proceedings of the 2022 Conference of the North American Chapter of the …, 2022	23	2022
NOPE: A corpus of naturally-occurring presuppositions in English A Parrish, S Schuster, A Warstadt, O Agha, SH Lee, Z Zhao, SR Bowman, ... arXiv preprint arXiv:2109.06987, 2021	23	2021
Paris and Stanford at EPE 2017: Downstream Evaluation of Graph-based Dependency Representations S Schuster, EV de la Clergerie, M Candito, B Sagot, CD Manning, ... Proceedings of the 2017 Shared Task on Extrinsic Parser Evaluation (EPE 2017), 2017	18	2017
Gapping Constructions in Universal Dependencies v2 S Schuster, M Lamm, CD Manning NoDaLiDa 2017 Workshop on Universal Dependencies (UDW 2017), 123-132, 2017	18	2017
Expectations over unspoken alternatives predict pragmatic inferences J Hu, R Levy, J Degen, S Schuster Transactions of the Association for Computational Linguistics 11, 2023	17	2023

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