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1
Societal Biases in Language Generation: Progress and Challenges ...
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2
Searching for an Effective Defender: Benchmarking Defense against Adversarial Word Substitution ...
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3
Does Robustness Improve Fairness? Approaching Fairness with Word Substitution Robustness Methods for Text Classification ...
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4
Intent Classification and Slot Filling for Privacy Policies ...
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5
Broaden the Vision: Geo-Diverse Visual Commonsense Reasoning ...
Abstract: Anthology paper link: https://aclanthology.org/2021.emnlp-main.162/ Abstract: Commonsense is defined as the knowledge that is shared by everyone. However, certain types of commonsense knowledge are correlated with culture and geographic locations and they are only shared locally. For example, the scenarios of wedding ceremonies vary across regions due to different customs influenced by historical and religious factors. Such regional characteristics, however, are generally omitted in prior work. In this paper, we construct a Geo-Diverse Visual Commonsense Reasoning dataset (GD-VCR) to test vision-and-language models' ability to understand cultural and geo-location-specific commonsense. In particular, we study two state-of-the-art Vision-and-Language models, VisualBERT and ViLBERT trained on VCR, a standard multimodal commonsense benchmark with images primarily from Western regions. We then evaluate how well the trained models can generalize to answering the questions in GD-VCR. We find that the performance of ...
Keyword: Computational Linguistics; Language Models; Machine Learning; Machine Learning and Data Mining; Natural Language Processing
URL: https://dx.doi.org/10.48448/2j0n-jf43
https://underline.io/lecture/37514-broaden-the-vision-geo-diverse-visual-commonsense-reasoning
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6
Ethical-Advice Taker: Do Language Models Understand Natural Language Interventions? ...
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7
Defense against Synonym Substitution-based Adversarial Attacks via Dirichlet Neighborhood Ensemble ...
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8
Improving Zero-Shot Cross-Lingual Transfer Learning via Robust Training ...
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9
Syntax-augmented Multilingual BERT for Cross-lingual Transfer ...
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10
BOLD: Dataset and Metrics for Measuring Biases in Open-Ended Language Generation ...
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11
Word and Sentence Embedding Tools to Measure Semantic Similarity of Gene Ontology Terms by Their Definitions.
In: Journal of computational biology : a journal of computational molecular cell biology, vol 26, iss 1 (2019)
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12
Retrofitting Contextualized Word Embeddings with Paraphrases ...
Shi, Weijia; Chen, Muhao; Zhou, Pei. - : arXiv, 2019
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13
Word and Sentence Embedding Tools to Measure Semantic Similarity of Gene Ontology Terms by Their Definitions
Duong, Dat; Ahmad, Wasi Uddin; Eskin, Eleazar. - : Mary Ann Liebert, Inc., publishers, 2019
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14
Efficient Contextual Representation Learning With Continuous Outputs
In: Transactions of the Association for Computational Linguistics, Vol 7, Pp 611-624 (2019) (2019)
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15
Word and Sentence Embedding Tools to Measure Semantic Similarity of Gene Ontology Terms by Their Definitions
In: Duong, Dat; Ahmad, Wasi Uddin; Eskin, Eleazar; Chang, Kai-Wei; & Li, Jingyi Jessica. (2018). Word and Sentence Embedding Tools to Measure Semantic Similarity of Gene Ontology Terms by Their Definitions. JOURNAL OF COMPUTATIONAL BIOLOGY, 26(1), 38 - 52. doi:10.1089/cmb.2018.0093. UCLA: Retrieved from: http://www.escholarship.org/uc/item/3j1294zk (2018)
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16
Man is to computer programmer as woman is to homemaker? debiasing word embeddings
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