Publications

International journals 

  • S. Delecraz, L. Becerra-Bonache, B. Favre, A. Nasr and F. Bechet: Multimodal Machine Learning for Natural Language Processing: Disambiguating Prepositional Phrase Attachments with Images. Neural Processing Letters, p. 1-28, 2020.
  • D. Angluin and L. Becerra-Bonache: A model of language learning with semantics and meaning-preserving corrections. Artificial Intelligence, 242: 23-51, 2017.
  • L. Becerra-Bonache and M. D. Jiménez-López:  Linguistic Models at the Crossroads of Agents, Learning and Formal Languages. ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 2014, vol. 3 num. 4, p. 67-87, 2014. PDF
  • L. Becerra-Bonache and M.D. Jiménez-López: An overview of the interrelation among Agents Systems, Learning Models and Formal Languages. LNCS Transactions on Computational Collective Intelligence, vol. 8790, 2014, p. 46-65, 2014. PDF
  • L. Becerra-Bonache, V. Dahl and J.E. Miralles: The role of Universal Constraints in Language Acquisition. FoLLI-LNCS series “Publications on Logic, Language and Information. Constraint Solving and Language Processing”, Springer, vol. 8114, p. 1-13, 2013. PDF
  • L. Becerra-Bonache, J. Case, S. Jain and F. Stephan: Iterative Learning of Simple External Contextual Languages. Theoretical Computer Science, vol. 411: 29-30, p. 2741-2756, 2010.  PDF
  • L. Becerra-Bonache, C. de la Higuera, J.C. Janodet and F. Tantini: Learning Balls of String from Edit Corrections. Journal of Machine Learning Research, vol. 9, p. 1841-1870, 2008. PDF

International conferences 

  • S. Delecraz, L. Becerra-Bonache, B. Favre, A. Nasr and F. Bechet: Visual Disambiguation of Preporsitional Phrase Attachments : Multimodal Machine Learning for Syntactic Analysis  Correction. IWANN : International Work-Conference on Artificial Neural Networks, p. 632-643, 2019.  PDF BEST PAPER AWARD
  • L. Becerra-Bonache, M.D. Jiménez-López: Natural Language Complexity and Machine Learning. DCAI 2018 : International Conference on Distributed Computing and Artificial Intelligence, p. 240-247, 2018. PDF
  • L. Becerra-Bonache, H. Blockeel, M. Galván, and F. Jacquenet: Learning language models from images with ReGLL. ECML/PKDD 2016: European Conference on Machine Learning and Knowledge Discovery in Databases, p. 55–58, 2016. PDF
  • L. Becerra-Bonache, H. Blockeel, M. Galván, and F. Jacquenet : Relational grounded language learning. ECAI 2016: European Conference on Artificial Intelligence, p. 1764-1765, 2016. PDF
  • L. Becerra-Bonache, H. Blockeel, M. Galván, F. Jacquenet, A First-Order-Logic Based Model for Grounded Language Learning. IDA 2015 : International Symposium on Intelligent Data Analysis, p. 49-60, 2015. PDF FRONTIER AWARD for the most visionary contribution of the conference.
  • L. Becerra-Bonache, M.D. Jiménez-López: A Grammatical Inference Model for Measuring Language Complexity. IWANN 2015: International Work-Conference on Artificial Neural Networks, p. 3-17, 2015. PDF
  • L. Becerra-Bonache, María Galván, François Jacquenet: A Proposal for Contextual Grammatical Inference. IWANN 2015: International Work-Conference on Artificial Neural Networks, p. 18-28, 2015. PDF
  • L. Becerra-Bonache, M.D. Jiménez-López: Learning, Agents and Formal Languages: Linguistic Applications of Interdisciplinary Fields. PAAMS 2015: Trends in Practical Applications of Heterogeneous Multi-agent Systems, p. 39-46, 2015.PDF
  • L. Becerra-Bonache: How can Grammatical Inference contribute to Computational Linguistics?. CIE 2014: Language, Life, Limits – 10th Conference on Computability in Europe, vol. 8493, 21-31, 2014. PDF
  • L. Becerra-Bonache, V. Dahl, M.D. Jiménez-López: Womb Grammars as a Bio-inspired Model for Grammar Induction. PAAMS 2014: International Conference on Practical Applications of Agents and Multi-Agent Systems, vol. 293, p. 79-86, 2014.PDF
  • L. Becerra-Bonache,  V. Dahl and J.E. Miralles: On Second Language Tutoring Through Womb Grammars. IWANN 2013: International Work-Conference on Artificial Neural Networks, vol. 7902, p. 189-197, 2013. PDF
  • L. Becerra-Bonache and M.D. Jiménez-López: Learning, Agents and Formal Languages: State of the Art. ICAART 2013: Int. Conference on Agents and Artificial Intelligence, p. 1-10, 2013.
  • L. Becerra-Bonache, E. Fromont, A. Habrard, M. Perrot and M. Sebban: Speeding up Syntactic Learning Using Contextual Information. ICGI 2012: International Colloquium on Grammatical Inference, 21: 49-53, 2012. PDF
  • D. Angluin and L. Becerra-Bonache: An Overview of How Semantics and Corrections Can Help Language Learning. WI-IAT 2011: IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, p. 147-150, 2011. PDF
  • D. Angluin and L. Becerra-Bonache: Effects of Meaning-Preserving Corrections on Language Learning. CoNLL 2011: 15th Conference on Computational Natural Language Learning, p. 97-105, 2011. PDF
  • L. Becerra-Bonache : Towards a Bio-computational Model of Language Learning. IWANN 2011: 11th International Work-Conference on Artificial Neural Networks, p. 473-480, 2011. PDF
  • L. Becerra-Bonache : Bio-inspired Grammatical Inference. IWINAC 2011: 4th International Work-Conference on the Interplay Between Natural and Artificial Computation, p. 313-322, 2011. PDF
  • L. Becerra-Bonache and M.D. Jiménez-López: Children as Models for Computers : Natural Language Acquisition for Machine Learning. ICAART 2011 : 3rd International Conference on Agents and Artificial Intelligence, p. 67-76, 2011. 
  • L. Becerra-Bonache, S. Bensch and M.D. Jiménez-López: L Systems as Bio-MAS for Natural Language Processing. PAAMS 2010: 8th International Conference on Practical Applications of Agents and Multi-Agent Systems, p. 395-402, 2010. PDF
  • L. Becerra-Bonache, S. Bensch and M.D. Jiménez-López: The Linguistic Relevance of Lindenmayer Systems. ICAART 2010: 2nd International Conference on Agents and Artificial Intelligence, p. 395-402, ISBN: 978-989-6-74-022-1, Depósito Legal: 303437/09, 2010. 
  • D. Angluin, L. Becerra-Bonache, A.H. Dediu and L. Reyzin: Learning Finite Automata Using Label Queries. ALT 2009: 20th International Conference on Algorithmic Learning Theory, LNCS, 5809, Springer, Berlin, p. 171-185, 2009.  PDF
  • L. Becerra-Bonache and A.H. Dediu: Learning from a Smarter Teacher. IDEAL 2009: 10th International Conference on Intelligent Data Engineering and Automated Learning, vol. 5788, p. 200-207, 2009.  PDF
  • L. Becerra-Bonache, J. Case, S. Jain and F. Stephan: Iterative Learning of Simple External Contextual Languages. ALT 2008: 19th International Conference on Algorithmic Learning Theory, LNCS, 5254, Springer, Berlin, p. 359-373, 2008. PDF
  • D. Angluin and L. Becerra-Bonache: Learning Meaning Before Syntax. ICGI 2008: 9th International Colloquium on Grammatical Inference, LNCS, 5278, Springer, Berlin, p. 1-14, 2008. PDF
  • D. Angluin, L. Becerra-Bonache: Using Semantic Information for Language Learning. ICDL 2007: 7th International Conference on Development and Learning, Monterrey, CA, USA, 2008.
  • L. Becerra-Bonache, C. de la Higuera, J.C. Janodet and F. Tantini: Learning Balls of Strings with Correction Queries. ECML 2007: 18th European Conference on Machine Learning, vol. 4701, p. 18-29, 2007.  PDF
  • T. Oates, T. Armstrong, L. Becerra-Bonache and M. Atamas: Inferring Grammars for Mildly Context Sensitive Languages in Polynomial-Time. ICGI 2006: 8th International Colloquium on Grammatical Inference, vol. 4201, p. 137-147, 2006. PDF
  • L. Becerra-Bonache, A.H. Dediu and C. Tirnauca: Learning DFA from Correction and Equivalence Queries. ICGI 2006: 8th International Colloquium on Grammatical Inference, vol. 4201, p. 281-292, 2006. PDF
  • L. Becerra-Bonache and T. Yokomori: Learning Mild Context-Sensitiveness: Toward Understanding Children’s Language Learning. ICGI 2004: 7th International Colloquium on Grammatical Inference, p. 53-64, 2004. PDF

National conferences

  • S. Delecraz, L. Becerra-Bonache, B. Favre, A. Nasr and F. Bechet: Correction automatique d’attachements prépositionnels par utilisation de traits visuels. TALN 2018: 25e Conférence sur le Traitement Automatique des Langues Naturelles, 2018.
  • S. Delecraz, L. Becerra-Bonache, B. Favre, A. Nasr and F. Bechet: Correction automatique d’attachements prépositionnels par utilisation de traits visuels. TALN 2018: 25e Conférence sur le Traitement Automatique des Langues Naturelles, 2018.
  • L. Becerra-Bonache, G. Bel-Enguix, M.D. Jiménez-López: Using Computers to Understand Natural Language Acquisition. AESLA 2010: 28th International Conference of the Spanish Society for Applied Linguistics, 2010.
  • L. Becerra-Bonache, G. Bel-Enguix, M.D. Jiménez-López: Using Computers to Understand Natural Language Acquisition. AESLA 2010: 28th International Conference of the Spanish Society for Applied Linguistics, 2010.
  • L. Becerra-Bonache, G. Bel-Enguix, M.D. Jiménez-López: Using Computers to Understand Natural Language Acquisition. AESLA 2010: 28th International Conference of the Spanish Society for Applied Linguistics, 2010.
  • L. Becerra-Bonache, G. Bel-Enguix, M.D. Jiménez-López: Using Computers to Understand Natural Language Acquisition. AESLA 2010: 28th International Conference of the Spanish Society for Applied Linguistics, 2010.

International workshops  

  • L. Becerra-Bonache, H. Christiansen and M. D. Jiménez-López : A Gold Standard to Measure Relative Linguistic Complexity with a Grounded Language Learning Model. COLING 2018 : Workshop on Linguistic Complexity and Natural Language Processing, p. 1-9, 2018.
  • L. Becerra-Bonache, H. Christiansen and M. D. Jiménez-López : A Gold Standard to Measure Relative Linguistic Complexity with a Grounded Language Learning Model. COLING 2018 : Workshop on Linguistic Complexity and Natural Language Processing, p. 1-9, 2018.
  • L. Becerra-Bonache, H. Christiansen and M. D. Jiménez-López : A Gold Standard to Measure Relative Linguistic Complexity with a Grounded Language Learning Model. COLING 2018 : Workshop on Linguistic Complexity and Natural Language Processing, p. 1-9, 2018.
  • L. Becerra-Bonache, H. Christiansen and M. D. Jiménez-López : A Gold Standard to Measure Relative Linguistic Complexity with a Grounded Language Learning Model. COLING 2018 : Workshop on Linguistic Complexity and Natural Language Processing, p. 1-9, 2018.
  • D. Angluin and L. Becerra-Bonache: Experiments Using OSTIA for a Language Production Task. CLAGI 2009: Workshop on Computational Linguistics Aspects of Grammatical Inference (in EACL 2009), Association for Computational Linguistics, p. 16-23, 2009.
  • D. Angluin and L. Becerra-Bonache: Experiments Using OSTIA for a Language Production Task. CLAGI 2009: Workshop on Computational Linguistics Aspects of Grammatical Inference (in EACL 2009), Association for Computational Linguistics, p. 16-23, 2009.
  • D. Angluin and L. Becerra-Bonache: Experiments Using OSTIA for a Language Production Task. CLAGI 2009: Workshop on Computational Linguistics Aspects of Grammatical Inference (in EACL 2009), Association for Computational Linguistics, p. 16-23, 2009.
  • D. Angluin and L. Becerra-Bonache: Experiments Using OSTIA for a Language Production Task. CLAGI 2009: Workshop on Computational Linguistics Aspects of Grammatical Inference (in EACL 2009), Association for Computational Linguistics, p. 16-23, 2009.
  • L. Becerra-Bonache, G. Bel-Enguix and M.D. Jiménez-López; From Natural Language Acquisition to Machine Learning and Back. MLCSLA 2007: Machine Learning and Cognitive Science of Language Acquisition, London, England, 2007.
  • L. Becerra-Bonache, G. Bel-Enguix and M.D. Jiménez-López; From Natural Language Acquisition to Machine Learning and Back. MLCSLA 2007: Machine Learning and Cognitive Science of Language Acquisition, London, England, 2007.
  • L. Becerra-Bonache, G. Bel-Enguix and M.D. Jiménez-López; From Natural Language Acquisition to Machine Learning and Back. MLCSLA 2007: Machine Learning and Cognitive Science of Language Acquisition, London, England, 2007.
  • L. Becerra-Bonache, G. Bel-Enguix and M.D. Jiménez-López; From Natural Language Acquisition to Machine Learning and Back. MLCSLA 2007: Machine Learning and Cognitive Science of Language Acquisition, London, England, 2007.
  • L. Becerra-Bonache, C. Bibire, A.H. Dediu: Learning DFA from corrections. TAGI 2005: Theoretical Aspects of Grammar Induction, Univ. of Tübingen, Germany, p. 1-12, 2005.

Book chapter 

  • L. Becerra-Bonache, G. Bel-Enguix, M.D. Jiménez-López, C. Martín-Vide: Formal Grammars and Languages. In R. Mitkov (Ed): The Oxford Handbook of Computational Linguistics (2nd Edition), Oxford University Press, p. 1-31, 2018. 
  • L. Becerra-Bonache, G. Bel-Enguix, M.D. Jiménez-López, C. Martín-Vide: Formal Grammars and Languages. In R. Mitkov (Ed): The Oxford Handbook of Computational Linguistics (2nd Edition), Oxford University Press, p. 1-31, 2018. 
  • L. Becerra-Bonache, G. Bel-Enguix, M.D. Jiménez-López, C. Martín-Vide: Formal Grammars and Languages. In R. Mitkov (Ed): The Oxford Handbook of Computational Linguistics (2nd Edition), Oxford University Press, p. 1-31, 2018. 

National Journals

  • L. Becerra-Bonache: Learning Simple External Contextual Languages from Only Positive Data. Triangle: Language – Mathematical Approaches, p. 1-18, 2012.
  • L. Becerra-Bonache: Learning Simple External Contextual Languages from Only Positive Data. Triangle: Language – Mathematical Approaches, p. 1-18, 2012.

Technical reports 

  • D. Angluin, L. Becerra-Bonache: A Model of Semantics and Corrections in Language Learning, YALEU/DCS/TR-1425, April, 2010.
  • D. Angluin, L. Becerra-Bonache: A Model of Semantics and Corrections in Language Learning, YALEU/DCS/TR-1425, April, 2010.