Methods › Natural Language Processing › Contextualized Word Embeddings › CoVe
Contextual Word Vectors
CoVe
Introduced by Bryan McCann et al. in Learned in Translation: Contextualized Word Vectors
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
CoVe, or Contextualized Word Vectors, uses a deep LSTM encoder from an attentional sequence-to-sequence model trained for machine translation to contextualize word vectors. CoVe word embeddings are therefore a function of the entire input sequence. These word embeddings can then be used in downstream tasks by concatenating them with GloVe embeddings:
v = [GloVe(x), CoVe(x)]
and then feeding these in as features for the task-specific models.
Papers archive 2025-07-28
13 shown of 13, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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CoVE: Compressed Vocabulary Expansion Makes Better LLM-based Recommender Systems 24 Jun 2025 · 1 repository · arXiv:2506.19993Syntology ran 0 of 4 samples · 4 unverified · 4 pointer-only (licence)
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COVE: COntext and VEracity prediction for out-of-context images 3 Feb 2025 · 2 repositories · arXiv:2502.01194Syntology ran 1 of 1 samples · 0 unverified
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On the Role of Surrogates in Conformal Inference of Individual Causal Effects 16 Dec 2024 · 1 repository · arXiv:2412.12365
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COVE: Unleashing the Diffusion Feature Correspondence for Consistent Video Editing 13 Jun 2024 · 1 repository · arXiv:2406.08850
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A Comprehensive Survey of Hallucination Mitigation Techniques in Large Language Models 2 Jan 2024 · 1 repository · arXiv:2401.01313Syntology ran 0 of 1 samples · 1 unverified
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Chain-of-Verification Reduces Hallucination in Large Language Models 20 Sep 2023 · 1 repository · arXiv:2309.11495
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Learning Category Trees for ID-Based Recommendation: Exploring the Power of Differentiable Vector Quantization 31 Aug 2023 · 2 repositories · arXiv:2308.16761
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FastFusionNet: New State-of-the-Art for DAWNBench SQuAD 28 Feb 2019 · 2 repositories · arXiv:1902.11291
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Language Modeling Teaches You More than Translation Does: Lessons Learned Through Auxiliary Syntactic Task Analysis 1 Nov 2018 · 0 repositories
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Language Modeling Teaches You More Syntax than Translation Does: Lessons Learned Through Auxiliary Task Analysis 26 Sep 2018 · 0 repositories · arXiv:1809.10040
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Improving Matching Models with Hierarchical Contextualized Representations for Multi-turn Response Selection 22 Aug 2018 · 0 repositories · arXiv:1808.07244
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Jiangnan at SemEval-2018 Task 11: Deep Neural Network with Attention Method for Machine Comprehension Task 1 Jun 2018 · 0 repositories
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Learned in Translation: Contextualized Word Vectors 1 Aug 2017 · 5 repositories · arXiv:1708.00107Syntology ran 3 of 3 samples · 0 unverified · 2 pointer-only (licence)
Tasks archive 2025-07-28
20 shown of 38 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
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