Are the Best Multilingual Document Embeddings simply Based on Sentence Embeddings? (2023.findings-eacl)
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| Challenge: | obtaining document embeddings at document level is challenging due to computational requirements and lack of appropriate data. |
| Approach: | They compare methods to produce document-level representations from sentences based on LASER, LaBSE, and Sentence BERT pre-trained multilingual models. |
| Outcome: | The proposed methods produce document-level representations from sentences in 8 languages . the results show that a clever combination of sentence embeddings is usually better than encoding the full document as a single unit. |
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| Challenge: | Existing methods for learning bilingual sentence embeddings are not well explored. |
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Cross-lingual Sentence Embedding using Multi-Task Learning (2021.emnlp-main)
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| Challenge: | Existing multilingual sentence embedding models require large parallel corpora to learn efficiently, limiting their scope. |
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| Challenge: | Embeddings have been a key topic of interest in NLP for the past decade . a quick warm-up introduction to NLP and why it is important to have a semantic comprehension of texts . |
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| Challenge: | Cross-lingual word embeddings are representations of words across languages in a shared continuous vector space. |
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| Challenge: | Existing methods to learn fixed-length embeddings for sentence semantics require large computational cost, making it difficult to process billions of sentences cost-efficiently or deploy models on resource-constrained devices such as smartphones. |
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| Challenge: | Obtaining sentence representations from BERT-based models is valuable as it takes less time to pre-compute a one-time representation of the data and then use it for the downstream tasks. |
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Give your Text Representation Models some Love: the Case for Basque (2020.lrec-1)
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Rodrigo Agerri, Iñaki San Vicente, Jon Ander Campos, Ander Barrena, Xabier Saralegi, Aitor Soroa, Eneko Agirre
| Challenge: | Word embeddings and pre-trained language models are expensive to train and are often used by small companies and research groups to build their own. |
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Aligning Cross-lingual Sentence Representations with Dual Momentum Contrast (2021.emnlp-main)
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| Challenge: | Existing work uses sentences within the same batch as negatives, which suffers from easy negatives. |
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