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1
Shared computational principles for language processing in humans and deep language models
In: Nat Neurosci (2022)
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2
Towards Zero-shot Language Modeling ...
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3
Designing an Automatic Agent for Repeated Language based Persuasion Games ...
Raifer, Maya; Rotman, Guy; Apel, Reut. - : arXiv, 2021
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4
Combining Deep Generative Models and Multi-lingual Pretraining for Semi-supervised Document Classification ...
Zhu, Yi; Shareghi, Ehsan; Li, Yingzhen. - : arXiv, 2021
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5
Are VQA Systems RAD? Measuring Robustness to Augmented Data with Focused Interventions ...
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6
Model Compression for Domain Adaptation through Causal Effect Estimation ...
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7
Parameter space factorization for zero-shot learning across tasks and languages ...
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8
Parameter space factorization for zero-shot learning across tasks and languages
In: Transactions of the Association for Computational Linguistics, 9 (2021)
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9
A Closer Look at Few-Shot Crosslingual Transfer: The Choice of Shots Matters ...
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10
Multi-SimLex: A Large-Scale Evaluation of Multilingual and Cross-Lingual Lexical Semantic Similarity
In: ISSN: 0891-2017 ; EISSN: 1530-9312 ; Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-02975786 ; Computational Linguistics, Massachusetts Institute of Technology Press (MIT Press), 2020, 46 (4), pp.847-897 ; https://direct.mit.edu/coli/article/46/4/847/97326/Multi-SimLex-A-Large-Scale-Evaluation-of (2020)
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11
Multidirectional Associative Optimization of Function-Specific Word Representations ...
Gerz, Daniela; Vulic, Ivan; Rei, Marek; Reichart, Roi; Korhonen, Anna; Linguist, Assoc Computat. - : Apollo - University of Cambridge Repository, 2020
Abstract: We present a neural framework for learning associations between interrelated groups of words such as the ones found in Subject-Verb-Object (SVO) structures. Our model induces a joint function-specific word vector space, where vectors of e.g. plausible SVO compositions lie close together. The model retains information about word group membership even in the joint space, and can thereby effectively be applied to a number of tasks reasoning over the SVO structure. We show the robustness and versatility of the proposed framework by reporting state-of-the-art results on the tasks of estimating selectional preference and event similarity. The results indicate that the combinations of representations learned with our task-independent model outperform task-specific architectures from prior work, while reducing the number of parameters by up to 95%. ...
URL: https://www.repository.cam.ac.uk/handle/1810/306833
https://dx.doi.org/10.17863/cam.53924
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12
CausaLM: Causal Model Explanation Through Counterfactual Language Models ...
Feder, Amir; Oved, Nadav; Shalit, Uri. - : arXiv, 2020
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13
A Closer Look at Few-Shot Crosslingual Transfer: The Choice of Shots Matters ...
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14
Multi-SimLex: A Large-Scale Evaluation of Multilingual and Cross-Lingual Lexical Semantic Similarity ...
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15
The Secret is in the Spectra: Predicting Cross-lingual Task Performance with Spectral Similarity Measures ...
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16
Multi-SimLex: A Large-Scale Evaluation of Multilingual and Cross-Lingual Lexical Semantic Similarity ...
Vulic, Ivan; Baker, Simon; Ponti, Edoardo. - : Apollo - University of Cambridge Repository, 2020
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17
The Secret is in the Spectra: Predicting Cross-Lingual Task Performance with Spectral Similarity Measures ...
Dubossarsky, Haim; Vulic, Ivan; Reichart, Roi. - : Apollo - University of Cambridge Repository, 2020
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18
The Secret is in the Spectra: Predicting Cross-Lingual Task Performance with Spectral Similarity Measures
Dubossarsky, Haim; Vulic, Ivan; Reichart, Roi. - : Association for Computational Linguistics, 2020. : Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP 2020), 2020
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19
Multidirectional Associative Optimization of Function-Specific Word Representations
Gerz, Daniela; Vulic, Ivan; Rei, Marek. - : Association for Computational Linguistics, 2020. : 58TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2020), 2020
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20
Modeling Language Variation and Universals: A Survey on Typological Linguistics for Natural Language Processing
In: ISSN: 0891-2017 ; EISSN: 1530-9312 ; Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-02425462 ; Computational Linguistics, Massachusetts Institute of Technology Press (MIT Press), 2019, 45 (3), pp.559-601. ⟨10.1162/coli_a_00357⟩ ; https://www.mitpressjournals.org/doi/abs/10.1162/coli_a_00357 (2019)
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