Papers with neural representation learning model
SphereRE: Distinguishing Lexical Relations with Hyperspherical Relation Embeddings (P19-1)
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| Challenge: | Lexical relations are relations between terms in lexicons. |
| Approach: | They propose a neural representation learning model to distinguish lexical relations among term pairs based on hyperspherical relation embeddings. |
| Outcome: | The proposed model outperforms state-of-the-art models on several benchmarks. |
Sentence Centrality Revisited for Unsupervised Summarization (P19-1)
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| Challenge: | Experimental results on three news summarization datasets representative of different languages and writing styles show that our approach outperforms strong baselines by a wide margin. |
| Approach: | They propose an unsupervised approach that uses a popular ranking algorithm to compute node centrality. |
| Outcome: | The proposed approach outperforms baselines on three news summarization datasets representative of different languages and writing styles. |