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[PDF] Top 20 Leveraging Synthetic Discourse Data via Multi task Learning for Implicit Discourse Relation Recognition

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Leveraging Synthetic Discourse Data via Multi task Learning for Implicit Discourse Relation Recognition

Leveraging Synthetic Discourse Data via Multi task Learning for Implicit Discourse Relation Recognition

... three multi-task learning systems outperformed single task learning systems, we find that the two synthetic implicit data sets have not been shown a universally ... See full document

10

Improving Implicit Discourse Relation Recognition with Discourse specific Word Embeddings

Improving Implicit Discourse Relation Recognition with Discourse specific Word Embeddings

... their discourse func- ...explicit data as additional training data via multi-task learning (Lan et ...or data selec- tion (Rutherford and Xue, 2015; Wu et ... See full document

6

Bilingually constrained Synthetic Data for Implicit Discourse Relation Recognition

Bilingually constrained Synthetic Data for Implicit Discourse Relation Recognition

... thetic implicit data (hereafter ...noise, via domain adaptation (Braud and De- nis, 2014; Ji et ...or multi-task learning (Lan et ... See full document

7

Adapting Event Embedding for Implicit Discourse Relation Recognition

Adapting Event Embedding for Implicit Discourse Relation Recognition

... the learning curve of the implicit classifier for all input types and architec- ...the learning curve in the development set reaches a higher ...training data set and combining multiple ... See full document

7

Employing the Correspondence of Relations and Connectives to Identify Implicit Discourse Relations via Label Embeddings

Employing the Correspondence of Relations and Connectives to Identify Implicit Discourse Relations via Label Embeddings

... such multi- task learning models for IDRR share the limi- tation of failing to exploit the mapping between the implicit connectives and the discourse rela- ...each implicit ... See full document

7

Improving Implicit Discourse Relation Classification by Modeling Inter dependencies of Discourse Units in a Paragraph

Improving Implicit Discourse Relation Classification by Modeling Inter dependencies of Discourse Units in a Paragraph

... lenging task of implicit discourse relation clas- sification when no explicit discourse connective phrase was ...two discourse units by exploiting interactions between words in ... See full document

11

Discourse Relation Prediction: Revisiting Word Pairs with Convolutional Networks

Discourse Relation Prediction: Revisiting Word Pairs with Convolutional Networks

... this task, as neural models are better at dealing with ...by learning linear and quadratic ...the discourse context by using an external ...joint learning, as the PDTB is a relatively small ... See full document

11

Multi task Attention based Neural Networks for Implicit Discourse Relationship Representation and Identification

Multi task Attention based Neural Networks for Implicit Discourse Relationship Representation and Identification

... the multi-task neural network by modifying the recurrent neural network for text classification ...a multi-task learn- ing based system which can effectively use syn- thetic data for ... See full document

10

The Effects of Discourse Connectives Prediction on Implicit Discourse Relation Recognition

The Effects of Discourse Connectives Prediction on Implicit Discourse Relation Recognition

... with implicit discourse relation recognition, there is no connective between the textual arguments, which results in a very difficult ...perform recognition without human-annotated ... See full document

8

Attention for Implicit Discourse Relation Recognition

Attention for Implicit Discourse Relation Recognition

... underlined discourse connective connects the first dis- course argument (in italic) to the second discourse argu- ment (in bold) via a temporal ...identify discourse relations. In fact, given ... See full document

6

Learning Connective based Word Representations for Implicit Discourse Relation Identification

Learning Connective based Word Representations for Implicit Discourse Relation Identification

... or multi-task al- gorithms (Lan et ...of data, the strategy requir- ing a large corpus of explicit examples to overcome the noise induced by the automatic annotation strat- ...explicit data ... See full document

11

Zero shot transfer for implicit discourse relation classification

Zero shot transfer for implicit discourse relation classification

... zero-shot learning in the implicit discourse relation classifi- cation ...training data is ...ing data from multiple ...for implicit discourse classification ... See full document

6

Implicit Discourse Relation Identification for Open domain Dialogues

Implicit Discourse Relation Identification for Open domain Dialogues

... course relation identification models on dialogue data and our proposed features, we build on the Deep Enhanced Representation (DER) model of Bai and Zhao (2018) 7 , which demonstrated its ef- ficiency by ... See full document

7

Interpretation of Chinese Discourse Connectives for Explicit Discourse Relation Recognition

Interpretation of Chinese Discourse Connectives for Explicit Discourse Relation Recognition

... two discourse units shown in (S1), ...two discourse units have differ- ent discourse relations when the single-word connectives appear at different positions, ...different discourse functions, ... See full document

12

Improving the Inference of Implicit Discourse Relations via Classifying Explicit Discourse Connectives

Improving the Inference of Implicit Discourse Relations via Classifying Explicit Discourse Connectives

... the data spar- sity problem is through a distantly supervised learn- ing paradigm, which is the direction we take in this ...labeled data, which potentially contain a small number of false ...labeled ... See full document

10

Implicit Discourse Relation Detection via a Deep Architecture with Gated Relevance Network

Implicit Discourse Relation Detection via a Deep Architecture with Gated Relevance Network

... the discourse relations held between text ...the data sparsity problem, the performance achieved by using word pair features is ...the data sparsity problem, we propose the use of word embeddings to ... See full document

10

Learning to Explicitate Connectives with Seq2Seq Network for Implicit Discourse Relation Classification

Learning to Explicitate Connectives with Seq2Seq Network for Implicit Discourse Relation Classification

... Implicit discourse relation classification is one of the most difficult steps in discourse ...coherence relation must be inferred based on the content of the discourse relational ... See full document

12

Acquiring Annotated Data with Cross lingual Explicitation for Implicit Discourse Relation Classification

Acquiring Annotated Data with Cross lingual Explicitation for Implicit Discourse Relation Classification

... a relation, while the German and the Czech translators didn’t do so), or that they propose the same coherence label: the human translation can introduce “noise” in the sense of the human trans- lators inferring ... See full document

10

Multi Task Transfer Learning for Weakly Supervised Relation Extraction

Multi Task Transfer Learning for Weakly Supervised Relation Extraction

... transfer learning for relation extraction, and we have achieved very promising ...transfer learning and adaptation for rela- tion extraction due to lack of training data in new domains, we ... See full document

9

Comparing Word Representations for Implicit Discourse Relation Classification

Comparing Word Representations for Implicit Discourse Relation Classification

... text data, thus alleviat- ing the need for hand-crafted lexical ...over discourse segments, comparing component-wise product against simple vector ... See full document

11

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