Papers by Anderson De Andrade
DENS: A Dataset for Multi-class Emotion Analysis (D19-1)
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| Challenge: | Existing sentence-level methods for emotion analysis are limited by the number of words in tweets and product reviews. |
| Approach: | They introduce a dataset for multi-class emotion analysis from long-form narratives in English . they use classic literature and modern online narratives available on Wattpad . |
| Outcome: | The proposed dataset provides a novel opportunity for emotion analysis that requires moving beyond sentence-level techniques. |
An Architecture for Accelerated Large-Scale Inference of Transformer-Based Language Models (2021.naacl-industry)
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| Challenge: | a recent paper shows that attention-based language models can be used to train, evaluate, and perform inference on predictive models. |
| Approach: | They develop a machine learning architecture that can scale to a large volume of requests . they use a BERT model that is fine-tuned for emotion analysis . |
| Outcome: | The proposed architecture can scale to a large volume of requests with a minimum of 96 hours of running time. |
Exploring Multilingual Syntactic Sentence Representations (D19-55)
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| Challenge: | Recent studies on language models that learn syntactic information focus on learning the semantic structures of language. |
| Approach: | They propose to use a multilingual parallel corpus augmented by universal part-of-speech tags to learn syntactic sentence embeddings. |
| Outcome: | The proposed method performs better than state-of-the-art language models in low-resource languages. |