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1
How does the pre-training objective affect what large language models learn about linguistic properties? ...
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Automatic Identification and Classification of Bragging in Social Media ...
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Analyzing Online Political Advertisements ...
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4
Modeling the Severity of Complaints in Social Media ...
Jin, Mali; Aletras, Nikolaos. - : arXiv, 2021
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5
Translation Error Detection as Rationale Extraction ...
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6
Knowledge Distillation for Quality Estimation ...
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7
Frustratingly Simple Pretraining Alternatives to Masked Language Modeling ...
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8
Analyzing Online Political Advertisements ...
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9
Improving the Faithfulness of Attention-based Explanations with Task-specific Information for Text Classification ...
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10
Enjoy the Salience: Towards Better Transformer-based Faithful Explanations with Word Salience ...
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11
Modeling the Severity of Complaints in Social Media ...
NAACL 2021 2021; Aletras, Nikolaos; Jin, Mali. - : Underline Science Inc., 2021
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12
Active Learning by Acquiring Contrastive Examples ...
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13
In Factuality: Efficient Integration of Relevant Facts for Visual Question Answering ...
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14
Frustratingly Simple Pretraining Alternatives to Masked Language Modeling ...
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15
Knowledge Distillation for Quality Estimation ...
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16
Machine Extraction of Tax Laws from Legislative Texts
In: Proceedings of the Natural Legal Language Processing Workshop 2021 (2021)
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17
Point-of-Interest Type Prediction using Text and Images ...
Abstract: Point-of-interest (POI) type prediction is the task of inferring the type of a place from where a social media post was shared. Inferring a POI's type is useful for studies in computational social science including sociolinguistics, geosemiotics, and cultural geography, and has applications in geosocial networking technologies such as recommendation and visualization systems. Prior efforts in POI type prediction focus solely on text, without taking visual information into account. However in reality, the variety of modalities, as well as their semiotic relationships with one another, shape communication and interactions in social media. This paper presents a study on POI type prediction using multimodal information from text and images available at posting time. For that purpose, we enrich a currently available data set for POI type prediction with the images that accompany the text messages. Our proposed method extracts relevant information from each modality to effectively capture interactions between text ... : Accepted at EMNLP 2021 ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://arxiv.org/abs/2109.00602
https://dx.doi.org/10.48550/arxiv.2109.00602
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18
Point-of-Interest Type Prediction using Text and Images ...
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19
An Empirical Study on Leveraging Position Embeddings for Target-oriented Opinion Words Extraction ...
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20
Knowledge distillation for quality estimation
Gajbhiye, Amit; Fomicheva, Marina; Alva-Manchego, Fernando. - : Association for Computational Linguistics, 2021
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