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1
Analyzing Gender Representation in Multilingual Models ...
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2
Universal Dependencies 2.9
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021
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Universal Dependencies 2.8.1
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021
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Universal Dependencies 2.8
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021
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5
BitFit: Simple Parameter-efficient Fine-tuning for Transformer-based Masked Language-models ...
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6
Including Signed Languages in Natural Language Processing ...
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7
Including Signed Languages in Natural Language Processing ...
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8
Contrastive Explanations for Model Interpretability ...
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9
Provable Limitations of Acquiring Meaning from Ungrounded Form: What will Future Language Models Understand? ...
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10
Measuring and Improving Consistency in Pretrained Language Models ...
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11
Aligning Faithful Interpretations with their Social Attribution ...
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12
Amnesic Probing: Behavioral Explanation With Amnesic Counterfactuals ...
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13
Data Augmentation for Sign Language Gloss Translation ...
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14
Effects of Parameter Norm Growth During Transformer Training: Inductive Bias from Gradient Descent ...
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15
Asking It All: Generating Contextualized Questions for any Semantic Role ...
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16
Counterfactual Interventions Reveal the Causal Effect of Relative Clause Representations on Agreement Prediction ...
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17
Neural Extractive Search ...
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18
Counterfactual Interventions Reveal the Causal Effect of Relative Clause Representations on Agreement Prediction ...
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19
Ab Antiquo: Neural Proto-language Reconstruction ...
NAACL 2021 2021; Goldberg, Yoav; Meloni, Carlo; Ravfogel, Shauli. - : Underline Science Inc., 2021
Abstract: Read the paper on the folowing link: https://www.aclweb.org/anthology/2021.naacl-main.353/ Abstract: Historical linguists have identified regularities in the process of historic sound change. The comparative method utilizes those regularities to reconstruct proto-words based on observed forms in daughter languages. Can this process be efficiently automated? We address the task of proto-word reconstruction, in which the model is exposed to cognates in contemporary daughter languages, and has to predict the proto word in the ancestor language. We provide a novel dataset for this task, encompassing over 8,000 comparative entries, and show that neural sequence models outperform conventional methods applied to this task so far. Error analysis reveals variability in the ability of neural model to capture different phonological changes, correlating with the complexity of the changes. Analysis of learned embeddings reveals the models learn phonologically meaningful generalizations, corresponding to well-attested ...
Keyword: Artificial Intelligence; Computer Science and Engineering; Intelligent System; Natural Language Processing; Psycholinguistics
URL: https://underline.io/lecture/19656-ab-antiquo-neural-proto-language-reconstruction
https://dx.doi.org/10.48448/7cw5-e737
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20
Simple, Interpretable and Stable Method for Detecting Words with Usage Change across Corpora
In: ACL 2020 - 58th Annual Meeting of the Association for Computational Linguistics ; https://hal.inria.fr/hal-03161637 ; ACL 2020 - 58th Annual Meeting of the Association for Computational Linguistics, Jul 2020, Seattle / Virtual, United States. pp.538-555, ⟨10.18653/v1/2020.acl-main.51⟩ (2020)
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