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1
Parameter-Efficient Neural Reranking for Cross-Lingual and Multilingual Retrieval ...
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2
Geographic Adaptation of Pretrained Language Models ...
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3
On cross-lingual retrieval with multilingual text encoders
Litschko, Robert; Vulić, Ivan; Ponzetto, Simone Paolo. - : Springer Science + Business Media, 2022
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4
Data for paper: "Evaluating Resource-Lean Cross-Lingual Embedding Models in Unsupervised Retrieval" ...
Litschko, Robert; Glavaš, Goran. - : Mannheim University Library, 2021
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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
On Cross-Lingual Retrieval with Multilingual Text Encoders ...
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7
Evaluating Multilingual Text Encoders for Unsupervised Cross-Lingual Retrieval ...
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8
RedditBias: A Real-World Resource for Bias Evaluation and Debiasing of Conversational Language Models ...
Abstract: Read paper: https://www.aclanthology.org/2021.acl-long.151 Abstract: Text representation models are prone to exhibit a range of societal biases, reflecting the non-controlled and biased nature of the underlying pretraining data, which consequently leads to severe ethical issues and even bias amplification. Recent work has predominantly focused on measuring and mitigating bias in pretrained language models. Surprisingly, the landscape of bias measurements and mitigation resources and methods for conversational language models is still very scarce: it is limited to only a few types of bias, artificially constructed resources, and completely ignores the impact that debiasing methods may have on the final perfor mance in dialog tasks, e.g., conversational response generation. In this work, we present REDDITBIAS, the first conversational data set grounded in the actual human conversations from Reddit, allowing for bias measurement and mitigation across four important bias dimensions: gender,race,religion, and ...
Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics
URL: https://underline.io/lecture/25465-redditbias-a-real-world-resource-for-bias-evaluation-and-debiasing-of-conversational-language-models
https://dx.doi.org/10.48448/b20r-x634
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9
LexFit: Lexical Fine-Tuning of Pretrained Language Models ...
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10
Verb Knowledge Injection for Multilingual Event Processing ...
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11
Is supervised syntactic parsing beneficial for language understanding tasks? An empirical investigation
Glavaš, Goran; Vulić, Ivan. - : Association for Computational Linguistics, 2021
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12
Evaluating multilingual text encoders for unsupervised cross-lingual retrieval
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13
Training and domain adaptation for supervised text segmentation
Glavaš, Goran; Ganesh, Ananya; Somasundaran, Swapna. - : Association for Computational Linguistics, 2021
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14
AraWEAT: Multidimensional Analysis of Biases in Arabic Word Embeddings ...
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15
XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning ...
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16
On the Limitations of Cross-lingual Encoders as Exposed by Reference-Free Machine Translation Evaluation ...
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17
Orthogonal Language and Task Adapters in Zero-Shot Cross-Lingual Transfer ...
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18
XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning ...
Ponti, Edoardo; Glavaš, Goran; Majewska, Olga. - : Apollo - University of Cambridge Repository, 2020
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19
From Zero to Hero: On the Limitations of Zero-Shot Cross-Lingual Transfer with Multilingual Transformers ...
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20
Verb Knowledge Injection for Multilingual Event Processing ...
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