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1
Did the Cat Drink the Coffee? Challenging Transformers with Generalized Event Knowledge
In: Proceedings of *SEM 2021: The Tenth Joint Conference on Lexical and Computational Semantics ; SEM 2021: The Tenth Joint Conference on Lexical and Computational Semantics ; https://hal.archives-ouvertes.fr/hal-03312774 ; SEM 2021: The Tenth Joint Conference on Lexical and Computational Semantics, Aug 2021, Online, France. pp.1-11, ⟨10.18653/v1/2021.starsem-1.1⟩ (2021)
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2
Not all arguments are processed equally: a distributional model of argument complexity
In: ISSN: 1574-020X ; EISSN: 1574-0218 ; Language Resources and Evaluation ; https://hal.archives-ouvertes.fr/hal-03533181 ; Language Resources and Evaluation, Springer Verlag, 2021, 55 (4), pp.873-900. ⟨10.1007/s10579-021-09533-9⟩ (2021)
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3
Not all arguments are processed equally: a distributional model of argument complexity
In: Springer Netherlands (2021)
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4
Decoding Word Embeddings with Brain-Based Semantic Features ...
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5
Did the Cat Drink the Coffee? Challenging Transformers with Generalized Event Knowledge ...
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6
Cognitive Aspects of the Lexicon (COGALEX-VI) ; Cognitive Aspects of the Lexicon (COGALEX-VI): Proceedings of the Workshop, December 12, 2020, Barcelona, Spain (Online)
In: https://hal.archives-ouvertes.fr/hal-03168880 ; 2020 (2020)
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7
Comparing Probabilistic, Distributional and Transformer-Based Models on Logical Metonymy Interpretation
In: Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing (AACL-IJCNLP) ; https://hal.archives-ouvertes.fr/hal-03042410 ; Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing (AACL-IJCNLP), Dec 2020, Suzhou, China (2020)
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8
A Structured Distributional Model of Sentence Meaning and Processing
In: ISSN: 1351-3249 ; EISSN: 1469-8110 ; Natural Language Engineering ; https://hal.archives-ouvertes.fr/hal-02151765 ; Natural Language Engineering, Cambridge University Press (CUP), 2019, 25, no. 4 (2019)
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9
Distributional Semantics Meets Construction Grammar. Towards a Unified Usage-Based Model of Grammar and Meaning
In: First International Workshop on Designing Meaning Representations (DMR 2019) ; https://hal.archives-ouvertes.fr/hal-02146537 ; First International Workshop on Designing Meaning Representations (DMR 2019), Aug 2019, Florence, Italy (2019)
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10
A Structured Distributional Model of Sentence Meaning and Processing ...
Abstract: Most compositional distributional semantic models represent sentence meaning with a single vector. In this paper, we propose a Structured Distributional Model (SDM) that combines word embeddings with formal semantics and is based on the assumption that sentences represent events and situations. The semantic representation of a sentence is a formal structure derived from Discourse Representation Theory and containing distributional vectors. This structure is dynamically and incrementally built by integrating knowledge about events and their typical participants, as they are activated by lexical items. Event knowledge is modeled as a graph extracted from parsed corpora and encoding roles and relationships between participants that are represented as distributional vectors. SDM is grounded on extensive psycholinguistic research showing that generalized knowledge about events stored in semantic memory plays a key role in sentence comprehension. We evaluate SDM on two recently introduced compositionality ... : accepted at JLNE; Journal of Natural Language Engineering; 26 pages, thematic fit, selectional preference, natural language processing, nlp, ai ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://dx.doi.org/10.48550/arxiv.1906.07280
https://arxiv.org/abs/1906.07280
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11
Event Knowledge in Sentence Processing: A New Dataset for the Evaluation of Argument Typicality
In: LREC 2018 Workshop on Linguistic and Neurocognitive Resources (LiNCR) ; https://hal.archives-ouvertes.fr/hal-01724286 ; LREC 2018 Workshop on Linguistic and Neurocognitive Resources (LiNCR), May 2018, Miyazaki, Japan (2018)
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12
Modeling Violations of Selectional Restrictions with Distributional Semantics
In: COLING Workshop on Linguistic Complexity and Natural Language Processing ; https://hal.archives-ouvertes.fr/hal-01838229 ; COLING Workshop on Linguistic Complexity and Natural Language Processing, Aug 2018, Santa Fe, United States (2018)
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13
Logical Metonymy in a Distributional Model of Sentence Comprehension
In: Proceedings of the Society for Computation in Linguistics (2018)
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14
Logical Metonymy in a Distributional Model of Sentence Comprehension
In: Proceedings of the 6th Joint Conference on Lexical and Computational Semantics ; Sixth Joint Conference on Lexical and Computational Semantics (*SEM 2017) ; https://hal.archives-ouvertes.fr/hal-01572187 ; Sixth Joint Conference on Lexical and Computational Semantics (*SEM 2017), Aug 2017, Vancouver, Canada. pp.168 - 177, ⟨10.18653/v1/S17-1021⟩ (2017)
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15
Measuring Thematic Fit with Distributional Feature Overlap
In: Proceedings of the Conference on Empirical Methods for Natural Language Processing 2017 ; https://hal.archives-ouvertes.fr/hal-01588246 ; Proceedings of the Conference on Empirical Methods for Natural Language Processing 2017, Sep 2017, Copenaghen, Denmark (2017)
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16
Testing APSyn against Vector Cosine on Similarity Estimation
In: PACLIC-2016 ; https://hal.archives-ouvertes.fr/hal-01462134 ; PACLIC-2016, 2016, Seoul, South Korea (2016)
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17
Representing Verbs with Rich Contexts: an Evaluation on Verb Similarity
In: EMNLP-2016 ; https://hal.archives-ouvertes.fr/hal-01462135 ; EMNLP-2016, 2016, Austin, United States (2016)
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18
Integrating distributional vectors into a construction-based framework
In: DSALT (Distributional Semantics and Linguistic Theory) ; https://hal.archives-ouvertes.fr/hal-01462160 ; DSALT (Distributional Semantics and Linguistic Theory), 2016, Bolzano, Italy. non paginé (2016)
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19
Towards a Distributional Model of Semantic Complexity
In: Proceedings of the COLING Workshop on Computational Linguistics for Linguistic Complexity ; COLING Workshop on Computational Linguistics for Linguistic Complexity ; https://hal.archives-ouvertes.fr/hal-01448957 ; COLING Workshop on Computational Linguistics for Linguistic Complexity, Dec 2016, Osaka, Japan. pp.12 - 22 (2016)
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20
Representing Verbs with Rich Contexts: an Evaluation on Verb Similarity ...
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