Marco Antonio Valenzuela-Escárcega

Affiliations:
  • University of Arizona, Tucson


According to our database1, Marco Antonio Valenzuela-Escárcega authored at least 28 papers between 2013 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

On csauthors.net:

Bibliography

2024
Active Learning Design Choices for NER with Transformers.
Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024

2022
From Examples to Rules: Neural Guided Rule Synthesis for Information Extraction.
CoRR, 2022

From Examples to Rules: Neural Guided Rule Synthesis for Information Extraction.
Proceedings of the Thirteenth Language Resources and Evaluation Conference, 2022

2020
AutoMATES: Automated Model Assembly from Text, Equations, and Software.
CoRR, 2020

Odinson: A Fast Rule-based Information Extraction Framework.
Proceedings of The 12th Language Resources and Evaluation Conference, 2020

Parsing as Tagging.
Proceedings of The 12th Language Resources and Evaluation Conference, 2020

MathAlign: Linking Formula Identifiers to their Contextual Natural Language Descriptions.
Proceedings of The 12th Language Resources and Evaluation Conference, 2020

An Unsupervised Method for Learning Representations of Multi-word Expressions for Semantic Classification.
Proceedings of the 28th International Conference on Computational Linguistics, 2020

2019
Eidos, INDRA, & Delphi: From Free Text to Executable Causal Models.
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.
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.
Proceedings of the Third Workshop on Structured Prediction for NLP@NAACL-HLT 2019, 2019

2018
Lightly-supervised Representation Learning with Global Interpretability.
CoRR, 2018

Large-scale automated machine reading discovers new cancer-driving mechanisms.
Database J. Biol. Databases Curation, 2018

Scientific Discovery as Link Prediction in Influence and Citation Graphs.
Proceedings of the Twelfth Workshop on Graph-Based Methods for Natural Language Processing, 2018

Text Annotation Graphs: Annotating Complex Natural Language Phenomena.
Proceedings of the Eleventh International Conference on Language Resources and Evaluation, 2018

2017
Learning what to read: Focused machine reading.
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.
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.
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, 2017

2016
Interpretable Models for Information Extraction.
PhD thesis, 2016

An investigation of coreference phenomena in the biomedical domain.
CoRR, 2016

Odin's Runes: A Rule Language for Information Extraction.
Proceedings of the Tenth International Conference on Language Resources and Evaluation LREC 2016, 2016

Sieve-based Coreference Resolution in the Biomedical Domain.
Proceedings of the Tenth International Conference on Language Resources and Evaluation LREC 2016, 2016

SnapToGrid: From Statistical to Interpretable Models for Biomedical Information Extraction.
Proceedings of the 15th Workshop on Biomedical Natural Language Processing, 2016

This before That: Causal Precedence in the Biomedical Domain.
Proceedings of the 15th Workshop on Biomedical Natural Language Processing, 2016

2015
Description of the Odin Event Extraction Framework and Rule Language.
CoRR, 2015

Two Practical Rhetorical Structure Theory Parsers.
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.
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.
Proceedings of the 2013 IEEE Third Joint International Conference on Development and Learning and Epigenetic Robotics, 2013


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