Shalom Lappin

Professor


Recent Papers

Shalom Lappin (2024), Assessing the Strengths and Weaknesses of Large Language Models, Journal of Logic, Language and Information, special issue Natural Logic Meets Machine Learning, Vol. 33, pp. 9-20.

Jean-Philippe Bernardy and Shalom Lappin (2023), Unitary Recurrent Networks: Algebraic and Linear Structures for Syntax in Shalom Lappin and Jean-Philippe Bernardy (eds), Algebraic Sturtures in Natural Language, CRC Press, Taylor and Francis, Boca Raton and Oxford, pp. 243-277.

Jean-Philippe Bernardy, Rasmus Blanck, Stergios Chatzikyriakidis, Shalom Lappin, and Aleksandre Maskharashvili (2022), Bayesian Inference Semantics for Natural Language in Jean-Philippe Bernardy, Rasmus Blanck, Stergios Chatzikyriakidis, Shalom Lappin, and Aleksandre Maskharashvili (eds.), Probabilistic Approaches to Linguistic Theory, CSLI Publications, Stanford CA, pp. 161-228.

Jean-Philippe Bernardy and Shalom Lappin (2022), Assessing the Unitary RNN as an End-to-End Compositional Model of Syntax in M. Moortgat and G. Wijnholds (eds), End-to-End Compositional Models of Vector-Based Semantics, 2022 (E2ECOMPVEC), Electronic Proceedings in Theoretical Computer Science 366.4, 2022, pp. 9–22.

Jean-Philippe Bernardy and Shalom Lappin (2022), A Neural Model for Compositional Word Embeddings and Sentence Processing, Proceedings of the Workshop on Cognitive Modeling and Computational Linguistics, May 26, 2022, Dublin, Association of Computational Linguistics, pp. 12--22.

Jey Han Lau, Carlos Armendariz, Shalom Lappin, Matthew Purver, and Chang Shu (2020), How Furiously Can Colorless Green Ideas Sleep? Sentence Acceptability in ContextTransactions of the Association for Computational Linguistics 8, pp. 296--310.

Adam Ek, Jean-Philippe Bernardy, and Shalom Lappin (2019), Language Modeling with Syntactic and Semantic Representation for Sentence Acceptability Predictions, Proceedings of the 22nd Nordic Conference on Computational Linguistics, September 30-October 2,
Turku, Finland, Linköping University Electronic Press, pp. 76-85.

Jean-Philippe Bernardy, Rasmus Blanck, Stergios Chatzikyriakidis, Shalom Lappin, and Aleksandre Maskharashvili (2019), Predicates as Boxes in Bayesian Semantics for Natural Language, Proceedings of the 22nd Nordic Conference on Computational Linguistics, September 30-October 2, Turku, Finland, Linköping University Electronic Press, pp. 333-337.

Jean-Philippe Bernardy, Rasmus Blanck, Stergios Chatzikyriakidis. Shalom Lappin, and Aleksandre Maskharashvili (2019), Bayesian Inference Semantics: A Modelling System and A Test Suite, Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (\SEM)*, pages 263--272 Minneapolis, July 6--7, 2019.

Yuri Bizzoni and Shalom Lappin (2019), Predicting Metaphor Paraphrase Judgements in Context, Proceedings of the 13th International Conference on Computational Semantics 2019 - Long Papers, University of Gothenburg, May 2019, pp. 165-174.

Shalom Lappin (2018), Towards a Computationally Viable Framework for Semantic Representation, Proceedings of the Symposium on Logic and Algorithms in Computational Linguistics 2018, September, 2018, Stockholm University, DiVA Portal for digital publications, pp. 47-63.

Yuri Bizzoni and Shalom Lappin (2018), The Effect of Context on Metaphor Paraphrase Aptness Judgments,  arXiv:1809.01060 [cs.CL], https://arxiv.org/abs/1809.01060.

Jean-Philippe Bernardy, Rasmus Blanck, Stergios Chatzikyriakidis, and Shalom Lappin (2018), A Compositional Bayesian Semantics for Natural Language, Proceedings of the First International Workshop on Language Cognition and Computational Models, COLING 2018, Santa Fe, New Mexico, August 20, 2018, pp. 1-10.

Shalom Lappin and Jey Han Lau (2018), Gradient Probabilistic Models vs Categorical Grammars: A Reply to Sprouse et al. (2018), The Science of Language (blog), July 2018, http://thescienceoflanguage.com/2018/07/22/gradient-probabilistic-models-vs-categorical-grammars-a-reply-to-sprouse-et-al-2018/.

Jean-Philippe Bernardy, Shalom Lappin, and Jey Han Lau (2018),The Influence of Context on Sentence Acceptability JudgementsProceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Short Papers), Melbourne, Australia, July 2018.

Yuri Bizzoni and Shalom Lappin (2018), Predicting Human Metaphor Paraphrase Judgments with Deep Neural Networks, Proceedings of the NAACL 2018 Workshop on Figurative Language Processing, New Orleans LA, June 2018, pp. 45-55.

Jean-Philippe Bernardy and Shalom Lappin (2017), Using Deep Neural Networks to Learn Syntactic Agreement, Linguistic Issues in Language Technology 15.2, pp. 1-15.

Yuri Bizzoni and Shalom Lappin (2017), Deep Learning of Binary and Gradient Judgements for Semantic Paraphrase, Proceedings of the International Workshop on Computational Semantics 2017, Montpellier, France, September 2017.

Jean-Philippe Bernardy and Shalom Lappin (2017), Learning Agreement with Deep Neural Networks, Israel Seminar on Computational Linguistics, Hebrew University of Jerusalem, September 2017.

Devdatt Dubhash and Shalom Lappin (2017), AI Dangers: Imagined and Real, Communications of the ACM, Vol 60. No. 2, February 2017, pp. 43-45.

Lau, Jey Han, Alexander Clark, and Shalom Lappin (2016), Grammaticality, Acceptability, and Probability: A Probabilistic View of Linguistic Knowledge, Cognitive Science, pp. 1-40.

Cooper, R., S. Dobnik, S. Lappin, and S. Larsson (2015), Probabilistic Type Theory and Natural Language Semantics, Linguistic Issues in Language Technology 10, pp. 1-43.

Lau, J.H., A. Clark, and S. Lappin (2015), Unsupervised Prediction of Acceptability Judgements, Proceedings of the 53rd Annual Conference of the Association of Computational Linguistics, Beijing, July 2015, pp. 1618-1628.

Lappin, S. (2015), Curry Typing, Polymorphism, and Fine-Grained Intensionality in S. Lappin and C. Fox (eds.), The Handbook of Contemporary Semantic Theory, Second Edition, Wiley-Blackwell, Oxford and Malden MA, pp. 408-428.

Fox, C. and S. Lappin (2015), Type-Theoretic Logic with an Operational Account of Intensionality, Synthèse 192, pp. 563-584 (The final publication is available at http://link.springer.com/article/10.1007/s11229-013-0390-1).

Lau, J. H., A. Clark, and S. Lappin (2014), Measuring Gradience in Speakers Grammaticality Judgements, Proceedings of the 36^th^ Annual Conference of the Cognitive Science Society, Quebec City, July 2014, pp. 821-826.

Cooper, R., S. Dobnik, S. Lappin, and S. Larsson (2014), A Probabilistic Rich Type Theory for Semantic Interpretation, Proceedings of the EACL 2014 Workshop on Type Theory and Natural Language Semantics (TTNLS), Gothenburg, April 2014, pp. 72¿79.

Lappin, S. (2013), Intensions as Computable Functions, Linguistic Issues in Language Technology 9, pp. 1-12.

Clark, A., G. Giorgolo, and S. Lappin (2013), Statistical Representation of Grammaticality Judgements: The Limits of N-Gram Models, Proceedings of the ACL Workshop on Cognitive Modelling and Computational Linguistics, Sophia, August 2013, pp. 28-36.

Clark, A., G. Giorgolo, and S. Lappin (2013), Towards a Statistical Model of Grammaticality, Proceedings of the 35^th^ Annual Conference of the Cognitive Science Society, Berlin, July-August 2013, pp. 2064-2069.

Clark, A. and S. Lappin (2013), Complexity in Language Acquisition, Topics in Cognitive Science 5, pp. 89-110.

Clark, A. and S. Lappin (2012), Computational Learning Theory and Language Acquisition in R. Kempson, N. Asher, and T. Fernando (eds.),Handbook of the Philosophy of Science, Volume 14: Philosophy of Linguistics, Elsevier, Oxford, pp. 445-475.

van Eijck, J. and S. Lappin (2012), Probabilistic Semantics for Natural Language, in Z. Christoff, P. Galeazzi, N. Gierasimszuk, A. Marcoci, and S. Smets (eds.),Logic and Interactive Rationality (LIRA) 2012, Volume 2, ILLC, University of Amsterdam, pp. 17-35.

Fox, C. and S. Lappin (2010), Expressiveness and Complexity in Underspecified Semantics, Linguistic Analysis 36, Festschrift for

Joachim Lambek, pp. 385-417 (information about this volume of Linguistic Analysis is available from info@linguisticanalysis.com).

Clark, A. and S. Lappin (2010), Unsupervised Learning and Grammar Induction in A. Clark, C. Fox, and S. Lappin (eds.), The Handbook of Computational Linguistics and Natural Language Processing, Wiley-Blackwell, Malden MA and Oxford, pp. 197-220.

Clark, A. and S. Lappin (2009), Another Look at Indirect Negative Evidence, Proceedings of the EACL Workshop on Cognitive Aspects of Computational Language Acquisition, Athens, March 2009, pp. 26-33.

Fernandez, R., J. Ginzburg, and S. Lappin (2007), Classifying Non-Sentential Utterances in Dialogue: A Machine Learning Approach, Computational Linguistics 33(3), pp. 397-427.

Lappin, S. and S. Shieber (2007), Machine Learning Theory and Practice as a Source of Insight into Universal Grammar, Journal of Linguistics 43(2), pp. 393-427. Copyright Cambridge University Press. Online issue of the Journal of Linguistics 43(2).

Fernandez, R., J. Ginzburg, H. Gregory, and S. Lappin (2007), SHARDS: Fragment Resolution in Dialogue in H. Bunt and R. Muskens (eds.), Computing Meaning Vol. 3, Springer, pp. 125-144.

Fox, C. and S. Lappin (2005), Achieving Expressive Completeness and Computational Efficiency for Underspecified Semantic Representations,Proceedings of The Fifteenth Amsterdam Colloquium, Amsterdam, pp. 77-82.

Lappin, S. (2005), Machine Learning and the Cognitive Basis of Natural Language, Proceedings of Computational Linguistics in the Netherlands 2004, Leiden, pp. 1-11.

Fernandez, R., J. Ginzburg, and S. Lappin (2005), Using Machine Learning for Non-Sentential Utterance Classification , Proceedings of SIGdial 6, Lisbon, pp. 77-86.

Fox, C. and S. Lappin (2005), Underspecified Interpretations in a Curry-Typed Representation Language, Journal of Logic and Computation 15, pp. 129-141.

Lappin, S. (2005), A Sequenced Model of Anaphora and Ellipsis Resolution in A. Branco, A, McEnery, and R. Mitkov (eds.), Anaphora Processing: Linguistic, Cognitive, and Computational Modelling, John Benjamins, Amsterdam, pp. 3-16.

Fernandez, R., J. Ginzburg, and S. Lappin (2005), Automatic Bare Sluice Disambiguation in Dialogue, Proceedings of the IWCS-6, Tilburg, pp. 115-127.

Fernandez, R., J. Ginzburg, and S. Lappin (2004), Classifying Ellipsis in Dialogue: A Machine Learning Approach, Proceedings of COLING 2004, Geneva, pp. 240-246.

Fox, C. and S. Lappin (2004), An Expressive First-Order Logic for Natural Language Semantics, Logic Journal of the International Group for Pure and Applied Logic 12, pp. 135-168.

Fox, C. and S. Lappin (2004), A Type-Theoretic Approach to Anaphora and Ellipsis Resolution, in  N. Nicolov, R. Mitkov, G. Angelova, and

K. Botcheva (eds.),  Recent Advances in Natural Language Processing IIISelected Papers from RANLP 2003, John Benjamins, Amsterdam, pp. 1-16.

Fox, C. and S. Lappin (2003), Doing Natural Language Semantics in an Expressive First-Order Logic with Flexible Typing in G. Jaeger, P. Monachesi, G. Penn, and S. Wintner (eds.), Proceedings of Formal Grammar 2003, Vienna, pp. 89-102.

Ebert, C., S. Lappin, H. Gregory, and N. Nicolov (2003), Full Parapharase Generation for Fragments in Dialogue in J. van Kuppevelt and R. Smith (eds.), Current and New Directions in Discourse and Dialogue, Kluwer, pp.161-181.

Fox, C., S. Lappin, and C. Pollard (2002), A Higher-Order Fine-Grained Logic for Intensional Semantics in G. Alberti, K. Balough, and P. Dekker (eds.), Proceedings of the Seventh Symposium for Logic and Language, Pecs, Hungary, pp.37-46.

Fox, C., S. Lappin, and C. Pollard (2002), Intensional First-Order Logic with Types in G. Alberti, K. Balough, and P. Dekker (eds.), Proceedings of the Seventh Symposium for Logic and Language, Pecs, Hungary, pp. 47-56.

Fox, C., S. Lappin, and C. Pollard (2002), First-Order Curry-Typed Logic for Natural Language Semantics in S. Wintner (ed.), Proceedings of the Workshop on Natural Language Understanding and Logic Programming, Copenhagen, pp. 87-102.

Fox, C. and S. Lappin (2001), A Framework for the Hyperintensional Semantics of Natural Language with Two Implementations in P. de Groote, G. Morrill, and C. Retore (eds.), Logical Aspects of Computational Linguistics, Springer Lecture Notes in Artificial Intelligence, Berlin and New York, pp. 175-192.