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Thomas Müller 0009
Person information
- affiliation: Google Research
- affiliation: LMU Munich, Center for Information and Language Processing
- affiliation: University of Stuttgart, Institute for Natural Language Processing
Other persons with the same name
- Thomas Müller — disambiguation page
- Thomas Müller 0001 — TU Munich, Faculty of Computer Science, Germany
- Thomas Müller 0002 — Eastphalia University of Applied Sciences, Braunschweig/Wolfenbüttel, Germany
- Thomas Müller 0003 — Friedrich Schiller University Jena, Institute of Computer Science, Germany
- Thomas Müller 0004 — Fraunhofer Institute for Optronics, System Technologies and Image Exploitation (IOSB), Karlsruhe, Germany
- Thomas Müller 0005
— Max Planck Institute for Astronomy, Heidelberg, Germany (and 1 more)
- Thomas Müller 0006 — University Hospital of Psychiatry, Bern, Switzerland
- Thomas Müller 0007
— Department of Philosophy, University of Konstanz, Germany (and 2 more)
- Thomas Müller 0008 — Daimler Research, Sindelfingen, Germany
- Thomas Müller 0010
— Forschungszentrum Jülich, Germany (and 1 more)
- Thomas Müller 0011 — University of Freiburg, Department for Applied Mathematics, Germany
- Thomas Müller 0012 — University of Karlsruhe, Germany
- Thomas Müller 0013
— NVIDIA Research, Zürich, Switzerland (and 2 more)
- Thomas Müller 0014 — Symanto Research, Nuremberg, Germany
- Thomas Müller 0015
— Mainz University of Applied Sciences, Germany
- Thomas Müller 0016 — Technical University Munich, Lehrstuhl für Rechnertechnik und Rechnerorganisation, Institute for Computer Science, Germany
- Thomas Müller 0017
— Goethe University and Senckenberg, Biodiversity and Climate Research Centre, Frankfurt, Germany
- Thomas Müller 0018 — University of Duisburg-Essen, Germany
- Thomas Müller 0019 — Technical University of Berlin, Institute of Ergonomics and Industrial Engineering, Germany
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2020 – today
- 2024
- [i9]Ryan Cotterell, Thomas Müller, Alexander Fraser, Hinrich Schütze:
Labeled Morphological Segmentation with Semi-Markov Models. CoRR abs/2404.08997 (2024) - [i8]Thomas Müller, Ryan Cotterell, Alexander Fraser, Hinrich Schütze:
Joint Lemmatization and Morphological Tagging with LEMMING. CoRR abs/2405.18308 (2024) - 2022
- [c17]Thomas Müller
, Guillermo Pérez-Torró
, Angelo Basile
, Marc Franco-Salvador
:
Active Few-Shot Learning with FASL. NLDB 2022: 98-110 - [c16]Mara Chinea-Rios
, Thomas Müller
, Gretel Liz De la Peña Sarracén
, Francisco Rangel
, Marc Franco-Salvador
:
Zero and Few-Shot Learning for Author Profiling. NLDB 2022: 333-344 - 2021
- [c15]Syrine Krichene, Thomas Müller, Julian Martin Eisenschlos:
DoT: An efficient Double Transformer for NLP tasks with tables. ACL/IJCNLP (Findings) 2021: 3273-3283 - [c14]Julian Martin Eisenschlos, Maharshi Gor, Thomas Müller, William W. Cohen:
MATE: Multi-view Attention for Table Transformer Efficiency. EMNLP (1) 2021: 7606-7619 - [c13]Jonathan Herzig, Thomas Müller, Syrine Krichene, Julian Martin Eisenschlos:
Open Domain Question Answering over Tables via Dense Retrieval. NAACL-HLT 2021: 512-519 - [c12]Thomas Müller, Julian Martin Eisenschlos, Syrine Krichene:
TAPAS at SemEval-2021 Task 9: Reasoning over tables with intermediate pre-training. SemEval@ACL/IJCNLP 2021: 423-430 - [i7]Jonathan Herzig, Thomas Müller, Syrine Krichene
, Julian Martin Eisenschlos:
Open Domain Question Answering over Tables via Dense Retrieval. CoRR abs/2103.12011 (2021) - [i6]Thomas Müller
, Julian Martin Eisenschlos, Syrine Krichene
:
TAPAS at SemEval-2021 Task 9: Reasoning over tables with intermediate pre-training. CoRR abs/2104.01099 (2021) - [i5]Syrine Krichene
, Thomas Müller
, Julian Martin Eisenschlos:
DoT: An efficient Double Transformer for NLP tasks with tables. CoRR abs/2106.00479 (2021) - [i4]Julian Martin Eisenschlos, Maharshi Gor, Thomas Müller, William W. Cohen:
MATE: Multi-view Attention for Table Transformer Efficiency. CoRR abs/2109.04312 (2021) - 2020
- [c11]Jonathan Herzig, Pawel Krzysztof Nowak, Thomas Müller
, Francesco Piccinno, Julian Martin Eisenschlos:
TaPas: Weakly Supervised Table Parsing via Pre-training. ACL 2020: 4320-4333 - [c10]Julian Martin Eisenschlos, Syrine Krichene, Thomas Müller
:
Understanding tables with intermediate pre-training. EMNLP (Findings) 2020: 281-296 - [i3]Jonathan Herzig, Pawel Krzysztof Nowak, Thomas Müller, Francesco Piccinno, Julian Martin Eisenschlos:
TAPAS: Weakly Supervised Table Parsing via Pre-training. CoRR abs/2004.02349 (2020) - [i2]Julian Martin Eisenschlos, Syrine Krichene
, Thomas Müller:
Understanding tables with intermediate pre-training. CoRR abs/2010.00571 (2020)
2010 – 2019
- 2019
- [c9]Thomas Müller
, Francesco Piccinno, Peter Shaw, Massimo Nicosia, Yasemin Altun:
Answering Conversational Questions on Structured Data without Logical Forms. EMNLP/IJCNLP (1) 2019: 5901-5909 - [i1]Thomas Müller, Francesco Piccinno, Massimo Nicosia, Peter Shaw, Yasemin Altun:
Answering Conversational Questions on Structured Data without Logical Forms. CoRR abs/1908.11787 (2019) - 2016
- [c8]Sebastian Ebert, Thomas Müller
, Hinrich Schütze:
LAMB: A Good Shepherd of Morphologically Rich Languages. EMNLP 2016: 742-752 - 2015
- [b1]Thomas Müller:
General methods for fine-grained morphological and syntactic disambiguation. Ludwig Maximilians University Munich, 2015 - [c7]Ryan Cotterell, Thomas Müller
, Alexander M. Fraser, Hinrich Schütze:
Labeled Morphological Segmentation with Semi-Markov Models. CoNLL 2015: 164-174 - [c6]Thomas Müller
, Ryan Cotterell, Alexander M. Fraser, Hinrich Schütze:
Joint Lemmatization and Morphological Tagging with Lemming. EMNLP 2015: 2268-2274 - [c5]Thomas Müller
, Hinrich Schütze:
Robust Morphological Tagging with Word Representations. HLT-NAACL 2015: 526-536 - 2014
- [c4]Thomas Müller
, Richárd Farkas, Alex Judea, Helmut Schmid, Hinrich Schütze:
Dependency parsing with latent refinements of part-of-speech tags. EMNLP 2014: 963-967 - 2013
- [c3]Thomas Müller, Helmut Schmid, Hinrich Schütze:
Efficient Higher-Order CRFs for Morphological Tagging. EMNLP 2013: 322-332 - 2012
- [c2]Thomas Müller, Hinrich Schütze, Helmut Schmid:
A Comparative Investigation of Morphological Language Modeling for the Languages of the European Union. HLT-NAACL 2012: 386-395 - 2011
- [c1]Thomas Müller, Hinrich Schütze:
Improved Modeling of Out-Of-Vocabulary Words Using Morphological Classes. ACL (2) 2011: 524-528
Coauthor Index
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last updated on 2024-08-27 22:57 CEST by the dblp team
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