Papers with natural language processing architectures
Content- and Topology-Aware Representation Learning for Scientific Multi-Literature (2023.emnlp-main)
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| Challenge: | Existing approaches focus on learning textual information at sentence- or document-level, but ignore inter-document connections. |
| Approach: | They propose a model that extends representation learning to the multi-document level . it integrates latent semantic and rich relatedness information from topological networks . |
| Outcome: | The proposed model learns latent semantic information from content and rich relatedness information from topological networks. |
Analyzing the Surprising Variability in Word Embedding Stability Across Languages (2021.emnlp-main)
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| Challenge: | Word embeddings are powerful representations that form the foundation of many natural language processing architectures. |
| Approach: | They explore word embedding stability in a wide range of languages to gain insight into their stability. |
| Outcome: | The proposed results provide insights into word embedding stability in English and other languages. |