Marco Antonio Valenzuela-Escárcega

According to our database, Marco Antonio Valenzuela-Escárcega authored at least 28 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Active Learning Design Choices for NER with Transformers.

Robert Vacareanu, Enrique Noriega-Atala, Gus Hahn-Powell, Marco Antonio Valenzuela-Escárcega, Mihai Surdeanu

Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024

2022

From Examples to Rules: Neural Guided Rule Synthesis for Information Extraction.

Robert Vacareanu, Marco Antonio Valenzuela-Escárcega, George Caique Gouveia Barbosa, Rebecca Sharp, Mihai Surdeanu

CoRR, 2022

From Examples to Rules: Neural Guided Rule Synthesis for Information Extraction.

Robert Vacareanu, Marco Antonio Valenzuela-Escárcega, George Caique Gouveia Barbosa, Rebecca Sharp, Gustave Hahn-Powell, Mihai Surdeanu

Proceedings of the Thirteenth Language Resources and Evaluation Conference, 2022

2020

AutoMATES: Automated Model Assembly from Text, Equations, and Software.

Adarsh Pyarelal, Marco Antonio Valenzuela-Escárcega, Rebecca Sharp, Paul Douglas Hein, Jon Stephens, Pratik Bhandari, HeuiChan Lim, Saumya Debray, Clayton T. Morrison

CoRR, 2020

Odinson: A Fast Rule-based Information Extraction Framework.

Marco Antonio Valenzuela-Escárcega, Gus Hahn-Powell, Dane Bell

Proceedings of The 12th Language Resources and Evaluation Conference, 2020

Parsing as Tagging.

Robert Vacareanu, George Caique Gouveia Barbosa, Marco Antonio Valenzuela-Escárcega, Mihai Surdeanu

Proceedings of The 12th Language Resources and Evaluation Conference, 2020

MathAlign: Linking Formula Identifiers to their Contextual Natural Language Descriptions.

Maria Alexeeva, Rebecca Sharp, Marco Antonio Valenzuela-Escárcega, Jennifer Kadowaki, Adarsh Pyarelal, Clayton T. Morrison

Proceedings of The 12th Language Resources and Evaluation Conference, 2020

An Unsupervised Method for Learning Representations of Multi-word Expressions for Semantic Classification.

Robert Vacareanu, Marco Antonio Valenzuela-Escárcega, Rebecca Sharp, Mihai Surdeanu

Proceedings of the 28th International Conference on Computational Linguistics, 2020

2019

Eidos, INDRA, & Delphi: From Free Text to Executable Causal Models.

Rebecca Sharp, Adarsh Pyarelal, Benjamin M. Gyori, Keith Alcock, Egoitz Laparra, Marco Antonio Valenzuela-Escárcega, Ajay Nagesh, Vikas Yadav, John A. Bachman, Zheng Tang, Heather C. Lent, Fan Luo, Mithun Paul, Steven Bethard, Kobus Barnard, Clayton T. Morrison, Mihai Surdeanu

Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

Enabling Search and Collaborative Assembly of Causal Interactions Extracted from Multilingual and Multi-domain Free Text.

George Caique Gouveia Barbosa, Zechy Wong, Gus Hahn-Powell, Dane Bell, Rebecca Sharp, Marco Antonio Valenzuela-Escárcega, Mihai Surdeanu

Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

Lightly-supervised Representation Learning with Global Interpretability.

Andrew Zupon, Maria Alexeeva, Marco Antonio Valenzuela-Escárcega, Ajay Nagesh, Mihai Surdeanu

Proceedings of the Third Workshop on Structured Prediction for NLP@NAACL-HLT 2019, 2019

2018

Lightly-supervised Representation Learning with Global Interpretability.

Marco Antonio Valenzuela-Escárcega, Ajay Nagesh, Mihai Surdeanu

CoRR, 2018

Large-scale automated machine reading discovers new cancer-driving mechanisms.

Marco Antonio Valenzuela-Escárcega, Özgün Babur, Gus Hahn-Powell, Dane Bell, Thomas Hicks, Enrique Noriega-Atala, Xia Wang, Mihai Surdeanu, Emek Demir, Clayton T. Morrison

Database J. Biol. Databases Curation, 2018

Scientific Discovery as Link Prediction in Influence and Citation Graphs.

Fan Luo, Marco Antonio Valenzuela-Escárcega, Gus Hahn-Powell, Mihai Surdeanu

Proceedings of the Twelfth Workshop on Graph-Based Methods for Natural Language Processing, 2018

Text Annotation Graphs: Annotating Complex Natural Language Phenomena.

Angus G. Forbes, Kristine Lee, Gus Hahn-Powell, Marco Antonio Valenzuela-Escárcega, Mihai Surdeanu

Proceedings of the Eleventh International Conference on Language Resources and Evaluation, 2018

2017

Learning what to read: Focused machine reading.

Enrique Noriega-Atala, Marco Antonio Valenzuela-Escárcega, Clayton T. Morrison, Mihai Surdeanu

Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017

Tell Me Why: Using Question Answering as Distant Supervision for Answer Justification.

Rebecca Sharp, Mihai Surdeanu, Peter Jansen, Marco Antonio Valenzuela-Escárcega, Peter Clark, Michael Hammond

Proceedings of the 21st Conference on Computational Natural Language Learning (CoNLL 2017), 2017

Swanson linking revisited: Accelerating literature-based discovery across domains using a conceptual influence graph.

Gus Hahn-Powell, Marco Antonio Valenzuela-Escárcega, Mihai Surdeanu

Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, 2017

2016

Interpretable Models for Information Extraction.

Marco Antonio Valenzuela-Escárcega

PhD thesis, 2016

An investigation of coreference phenomena in the biomedical domain.

Dane Bell, Gus Hahn-Powell, Marco Antonio Valenzuela-Escárcega, Mihai Surdeanu

CoRR, 2016

Odin's Runes: A Rule Language for Information Extraction.

Marco Antonio Valenzuela-Escárcega, Gus Hahn-Powell, Mihai Surdeanu

Proceedings of the Tenth International Conference on Language Resources and Evaluation LREC 2016, 2016

Sieve-based Coreference Resolution in the Biomedical Domain.

Dane Bell, Gus Hahn-Powell, Marco Antonio Valenzuela-Escárcega, Mihai Surdeanu

Proceedings of the Tenth International Conference on Language Resources and Evaluation LREC 2016, 2016

SnapToGrid: From Statistical to Interpretable Models for Biomedical Information Extraction.

Marco Antonio Valenzuela-Escárcega, Gus Hahn-Powell, Dane Bell, Mihai Surdeanu

Proceedings of the 15th Workshop on Biomedical Natural Language Processing, 2016

This before That: Causal Precedence in the Biomedical Domain.

Gus Hahn-Powell, Dane Bell, Marco Antonio Valenzuela-Escárcega, Mihai Surdeanu

Proceedings of the 15th Workshop on Biomedical Natural Language Processing, 2016

2015

Description of the Odin Event Extraction Framework and Rule Language.

Marco Antonio Valenzuela-Escárcega, Gus Hahn-Powell, Mihai Surdeanu

CoRR, 2015

Two Practical Rhetorical Structure Theory Parsers.

Mihai Surdeanu, Tom Hicks, Marco Antonio Valenzuela-Escárcega

Proceedings of the NAACL HLT 2015, The 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Denver, Colorado, USA, May 31, 2015

A Domain-independent Rule-based Framework for Event Extraction.

Marco Antonio Valenzuela-Escárcega, Gus Hahn-Powell, Mihai Surdeanu, Thomas Hicks

Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, 2015

2013

A generative probabilistic framework for learning spatial language.

Colin R. Dawson, Jeremy B. Wright, Antons Rebguns, Marco Antonio Valenzuela-Escárcega, Daniel Fried, Paul R. Cohen

Proceedings of the 2013 IEEE Third Joint International Conference on Development and Learning and Epigenetic Robotics, 2013