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The Devil is in the Details: Evaluating Limitations of Transformer-based Methods for Granular Tasks
Contextual embeddings derived from transformer-based neural language mod...
11/02/2020 ∙ by Brihi Joshi, et al. ∙
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Efficiently Mitigating Classification Bias via Transfer Learning
Prediction bias in machine learning models refers to unintended model be...
10/24/2020 ∙ by Xisen Jin, et al. ∙
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TweetEval: Unified Benchmark and Comparative Evaluation for Tweet Classification
The experimental landscape in natural language processing for social med...
10/23/2020 ∙ by Francesco Barbieri, et al. ∙
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Learning Cross-lingual Embeddings from Twitter via Distant Supervision
Cross-lingual embeddings represent the meaning of words from different l...
05/17/2019 ∙ by Jose Camacho-Collados, et al. ∙
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Exploring Emoji Usage and Prediction Through a Temporal Variation Lens
The frequent use of Emojis on social media platforms has created a new f...
05/02/2018 ∙ by Francesco Barbieri, et al. ∙
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Multimodal Emoji Prediction
Emojis are small images that are commonly included in social media text ...
03/06/2018 ∙ by Francesco Barbieri, et al. ∙
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Are Emojis Predictable?
Emojis are ideograms which are naturally combined with plain text to vis...
02/23/2017 ∙ by Francesco Barbieri, et al. ∙
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