581 |
Multilingual Irony Detection with Dependency Syntax and Neural Models ...
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582 |
SaSAKE: Syntax and Semantics Aware Keyphrase Extraction from Research Papers ...
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583 |
Sampling, Syntax, and Sentence Completions.The (Overlooked?) Impact of Gender on NLP Tools ...
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584 |
Syntax-Aware Graph Attention Network for Aspect-Level Sentiment Classification ...
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585 |
Bridging the Gap in Multilingual Semantic Role Labeling: A Language-Agnostic Approach ...
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586 |
Syntactically Aware Cross-Domain Aspect and Opinion Terms Extraction ...
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587 |
Exploring diachronic syntactic shifts with dependency length: the case of scientific English ...
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589 |
Style Analysis of Argumentative Texts by Mining Rhetorical Devices ...
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590 |
Anaphoric Zero Pronoun Identification: A Multilingual Approach ...
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591 |
Collective Wisdom: Improving Low-resource Neural Machine Translationusing Adaptive Knowledge Distillation ...
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592 |
Learning to Decouple Relations: Few-Shot Relation Classification with entity-Guided Attention and Confusion-Aware Training ...
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Abstract:
This paper aims to enhance the few-shot relation classification especially for sentences that jointly describe multiple relations. Due to the fact that some relations usually keep high co-occurrence in the same context, previous few-shot relation classifiers struggle to distinguish them with few annotated instances. To alleviate the above relation confusion problem, we propose tag, a model equipped with two mechanisms to learn to decouple these easily-confused relations. On the one hand, an anEntity-GuidedAttention (EGA) mechanism, which leverages the syntactic relations and relative positions between each word and the specified entity pair, is introduced to guide the attention to filter out information causing confusion. On the other hand, a Confusion-AwareTraining (CAT) method is proposed to explicitly learn to distinguish relations by playing a pushing-away game between classifying a sentence into a true relation and its con-fusing relation. Extensive experiments are conducted on the FewRel dataset, and ...
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Keyword:
Computer and Information Science; Natural Language Processing; Neural Network
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URL: https://underline.io/lecture/6126-learning-to-decouple-relations-few-shot-relation-classification-with-entity-guided-attention-and-confusion-aware-training https://dx.doi.org/10.48448/xdjy-cv58
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596 |
Automatic Topological Field Identification in (Historical) German Texts ...
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597 |
A Semantically Consistent and Syntactically Variational Encoder-Decoder Framework for Paraphrase Generation ...
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598 |
Understanding the effects of word-level linguistic annotations in under-resourced neural machine translation ...
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600 |
Variation in Coreference Strategies across Genres and Production Media ...
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