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1
Delving Deeper into Cross-lingual Visual Question Answering ...
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2
Cross-Lingual Dialogue Dataset Creation via Outline-Based Generation ...
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3
Improving Word Translation via Two-Stage Contrastive Learning ...
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4
Towards Zero-shot Language Modeling ...
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5
Crossing the Conversational Chasm: A Primer on Natural Language Processing for Multilingual Task-Oriented Dialogue Systems ...
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6
Learning Domain-Specialised Representations for Cross-Lingual Biomedical Entity Linking ...
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7
MirrorWiC: On Eliciting Word-in-Context Representations from Pretrained Language Models ...
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8
Parameter space factorization for zero-shot learning across tasks and languages ...
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9
MirrorWiC: On Eliciting Word-in-Context Representations from Pretrained Language Models ...
Liu, Qianchu; Liu, Fangyu; Collier, Nigel. - : Apollo - University of Cambridge Repository, 2021
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10
Learning Domain-Specialised Representations for Cross-Lingual Biomedical Entity Linking ...
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11
MirrorWiC: On Eliciting Word-in-Context Representations from Pretrained Language Models ...
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12
Semantic Data Set Construction from Human Clustering and Spatial Arrangement ...
Majewska, Olga; McCarthy, Diana; Van Den Bosch, Jasper JF. - : Apollo - University of Cambridge Repository, 2021
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13
AM2iCo: Evaluating Word Meaning in Context across Low-Resource Languages with Adversarial Examples ...
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14
Fast, Effective, and Self-Supervised: Transforming Masked Language Models into Universal Lexical and Sentence Encoders ...
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15
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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16
AM2iCo: Evaluating Word Meaning in Context across Low-Resource Languages with Adversarial Examples ...
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17
Fast, Effective, and Self-Supervised: Transforming Masked Language Models into Universal Lexical and Sentence Encoders ...
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18
LexFit: Lexical Fine-Tuning of Pretrained Language Models ...
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19
Verb Knowledge Injection for Multilingual Event Processing ...
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20
A Closer Look at Few-Shot Crosslingual Transfer: The Choice of Shots Matters ...
Abstract: Read paper: https://www.aclanthology.org/2021.acl-long.447 Abstract: Few-shot crosslingual transfer has been shown to outperform its zero-shot counterpart with pretrained encoders like multilingual BERT. Despite its growing popularity, little to no attention has been paid to standardizing and analyzing the design of few-shot experiments. In this work, we highlight a fundamental risk posed by this shortcoming, illustrating that the model exhibits a high degree of sensitivity to the selection of few shots. We conduct a large-scale experimental study on 40 sets of sampled few shots for six diverse NLP tasks across up to 40 languages. We provide an analysis of success and failure cases of few-shot transfer, which highlights the role of lexical features. Additionally, we show that a straightforward full model finetuning approach is quite effective for few-shot transfer, outperforming several state-of-the-art few-shot approaches. As a step towards standardizing few-shot crosslingual experimental designs, we make ...
Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics
URL: https://underline.io/lecture/25886-a-closer-look-at-few-shot-crosslingual-transfer-the-choice-of-shots-matters
https://dx.doi.org/10.48448/m8s0-3a39
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