Papers with sentence encoding
Exploiting WordNet Synset and Hypernym Representations for Answer Selection (2020.aacl-main)
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| Challenge: | Answer selection (AS) is a challenging subtask of document-based question answering (DQA). |
| Approach: | They propose to use WordNet to enrich the word representation and sentence encoding to incorporate similarity scores of two concepts that share synset or hypernym relations into the attention mechanism. |
| Outcome: | The proposed model outperforms existing state-of-the-art models on the public WikiQA and SelQA datasets and significantly improves the baseline system. |
A Novel Aspect-Guided Deep Transition Model for Aspect Based Sentiment Analysis (D19-1)
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| Challenge: | Existing models use aspect-independent encoders for sentence representation generation. |
| Approach: | They propose an aspect-guided deep transition model which guides the sentence encoding from scratch with a specially-designed deep transition architecture. |
| Outcome: | The proposed model outperforms existing models on multiple datasets on aspect-category sentiment analysis and aspectterm sentiment analysis without additional features. |
Comparative Study of Sentence Embeddings for Contextual Paraphrasing (2020.lrec-1)
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| Challenge: | Paraphrasing is an important aspect of natural-language generation that can produce more variety in the way specific content is presented. |
| Approach: | They propose to use contextual paraphrasing to capture the meaning of a sentence while performing dialogue act clustering. |
| Outcome: | The proposed task combines paraphrases with dialogue act clustering to capture such contextual paraphrasing. |