Papers with sentence-level embeddings
Universal Sentence Encoder for English (D18-2)
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Daniel Cer, Yinfei Yang, Sheng-yi Kong, Nan Hua, Nicole Limtiaco, Rhomni St. John, Noah Constant, Mario Guajardo-Cespedes, Steve Yuan, Chris Tar, Brian Strope, Ray Kurzweil
| Challenge: | TensorFlow Hub sentence embedding models have good task transfer performance . model variants allow for trade-offs between accuracy and compute resources . |
| Approach: | They propose easy-to-use TensorFlow Hub sentence embedding models with good task transfer performance. |
| Outcome: | The proposed models outperform models without transfer learning and those that use only word-level transfer on a number of NLP tasks. |
Learning Semantic Sentence Embeddings using Sequential Pair-wise Discriminator (C18-1)
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| Challenge: | a novel method for obtaining sentence-level embeddings is proposed . the problem of obtaining a semantic embeddable sentence is at the core of understanding languages . |
| Approach: | They propose a method for obtaining sentence-level embeddings by using a sequential encoder-decoder framework. |
| Outcome: | The proposed method outperforms the state-of-the-art on a sentiment analysis task. |
COSTRA 1.0: A Dataset of Complex Sentence Transformations (2020.lrec-1)
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| Challenge: | Several studies have shown word vector representations capture syntactic and semantic regularities. |
| Approach: | They present a dataset of sentence-level embeddings in Czech and plan to use it in other languages. |
| Outcome: | The proposed dataset is limited to Czech but will be used in other languages. |
Improving Event Coreference Resolution Using Document-level and Topic-level Information (2022.emnlp-main)
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| Challenge: | Experimental results show that our model outperforms the SOTA baselines due to the encoding length limitation. |
| Approach: | They propose a longformer-based encoder and an encoder with a trigger-mask mechanism to learn sentence-level embeddings based on local context. |
| Outcome: | The proposed model outperforms the baselines on the KBP 2017 dataset. |