Deep enhanced representation for implicit discourse relation recognition
Implicit discourse relation recognition is a challenging task as the relation prediction without
explicit connectives in discourse parsing needs understanding of text spans and cannot be …
explicit connectives in discourse parsing needs understanding of text spans and cannot be …
Conll 2016 shared task on multilingual shallow discourse parsing
Abstract The CoNLL-2016 Shared Task is the second edition of the CoNLL-2015 Shared
Task, now on Multilingual Shallow discourse parsing. Similar to the 2015 task, the goal of …
Task, now on Multilingual Shallow discourse parsing. Similar to the 2015 task, the goal of …
Adversarial connective-exploiting networks for implicit discourse relation classification
Implicit discourse relation classification is of great challenge due to the lack of connectives
as strong linguistic cues, which motivates the use of annotated implicit connectives to …
as strong linguistic cues, which motivates the use of annotated implicit connectives to …
Facilitating contrastive learning of discourse relational senses by exploiting the hierarchy of sense relations
Implicit discourse relation recognition is a challenging task that involves identifying the
sense or senses that hold between two adjacent spans of text, in the absence of an explicit …
sense or senses that hold between two adjacent spans of text, in the absence of an explicit …
[PDF][PDF] A stacking gated neural architecture for implicit discourse relation classification
Discourse parsing is considered as one of the most challenging natural language
processing (NLP) tasks. Implicit discourse relation classification is the bottleneck for …
processing (NLP) tasks. Implicit discourse relation classification is the bottleneck for …
Global and local hierarchy-aware contrastive framework for implicit discourse relation recognition
Due to the absence of explicit connectives, implicit discourse relation recognition (IDRR)
remains a challenging task in discourse analysis. The critical step for IDRR is to learn high …
remains a challenging task in discourse analysis. The critical step for IDRR is to learn high …
Implicit discourse relation recognition using neural tensor network with interactive attention and sparse learning
Implicit discourse relation recognition aims to understand and annotate the latent relations
between two discourse arguments, such as temporal, comparison, etc. Most previous …
between two discourse arguments, such as temporal, comparison, etc. Most previous …
A systematic study of neural discourse models for implicit discourse relation
Inferring implicit discourse relations in natural language text is the most difficult subtask in
discourse parsing. Many neural network models have been proposed to tackle this problem …
discourse parsing. Many neural network models have been proposed to tackle this problem …
Transs-driven joint learning architecture for implicit discourse relation recognition
R He, J Wang, F Guo, Y Han - … of the 58th Annual Meeting of the …, 2020 - aclanthology.org
Implicit discourse relation recognition is a challenging task due to the lack of connectives as
strong linguistic clues. Previous methods primarily encode two arguments separately or …
strong linguistic clues. Previous methods primarily encode two arguments separately or …
Working memory-driven neural networks with a novel knowledge enhancement paradigm for implicit discourse relation recognition
Recognizing implicit discourse relation is a challenging task in discourse analysis, which
aims to understand and infer the latent relations between two discourse arguments, such as …
aims to understand and infer the latent relations between two discourse arguments, such as …