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Character Alignment in Morphologically Complex Translation Sets for Related Languages ...
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3 |
Composing Byte-Pair Encodings for Morphological Sequence Classification ...
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Variation in Universal Dependencies annotation: A token based typological case study on adpossessive constructions ...
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5 |
Corpus evidence for word order freezing in Russian and German ...
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Noise Isn't Always Negative: Countering Exposure Bias in Sequence-to-Sequence Inflection Models ...
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8 |
Exhaustive Entity Recognition for Coptic - Challenges and Solutions ...
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9 |
Imagining Grounded Conceptual Representations from Perceptual Information in Situated Guessing Games ...
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10 |
Attentively Embracing Noise for Robust Latent Representation in BERT ...
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13 |
Classifier Probes May Just Learn from Linear Context Features ...
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14 |
Seeing the world through text: Evaluating image descriptions for commonsense reasoning in machine reading comprehension ...
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16 |
Manifold Learning-based Word Representation Refinement Incorporating Global and Local Information ...
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Abstract:
Recent studies show that word embedding models often underestimate similarities between similar words and overestimate similarities between distant words. This results in word similarity results obtained from embedding models inconsistent with human judgment. Manifold learningbased methods are widely utilized to refine word representations by re-embedding word vectors from the original embedding space to a new refined semantic space. These methods mainly focus on preserving local geometry information through performing weighted locally linear combination between words and their neighbors twice. However, these reconstruction weights are easily influenced by different selections of neighboring words and the whole combination process is time-consuming. In this paper, we propose two novel word representation refinement methods leveraging isometry feature mapping and local tangent space respectively. Unlike previous methods, our first method corrects pre-trained word embeddings by preserving global geometry ...
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Keyword:
Computer and Information Science; Natural Language Processing; Neural Network
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URL: https://underline.io/lecture/6371-manifold-learning-based-word-representation-refinement-incorporating-global-and-local-information https://dx.doi.org/10.48448/zdmt-5609
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17 |
HMSid and HMSid2 at PARSEME Shared Task 2020: Computational Corpus Linguistics and unseen-in-training MWEs ...
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18 |
Multi-dialect Arabic BERT for Country-level Dialect Identification ...
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20 |
Exploring End-to-End Differentiable Natural Logic Modeling ...
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