Papers Implicit Discourse Relation Classification
“Implicit Discourse Relation Classification” 태그가 달린 논문 37편 · 필터 해제
Implicit Discourse Relation Classification For Nigerian Pidgin
Despite attempts to make Large Language Models multi-lingual, many of the world's languages are still severely under-resourced. This widens the performance gap between NLP and AI applications aimed at well-financed, and …
ClassificationImplicit Discourse Relation ClassificationRelationRelation ClassificationPrompting Implicit Discourse Relation Annotation
Pre-trained large language models, such as ChatGPT, archive outstanding performance in various reasoning tasks without supervised training and were found to have outperformed crowdsourcing workers. Nonetheless, ChatGPT's…
ClassificationImplicit Discourse Relation ClassificationMultiple-choicePrompt Engineering+2A Side-by-side Comparison of Transformers for English Implicit Discourse Relation Classification
Though discourse parsing can help multiple NLP fields, there has been no wide language model search done on implicit discourse relation classification. This hinders researchers from fully utilizing public-available model…
Discourse ParsingImplicit Discourse Relation ClassificationLanguage ModelingLanguage Modelling+3Annotation-Inspired Implicit Discourse Relation Classification with Auxiliary Discourse Connective Generation
Implicit discourse relation classification is a challenging task due to the absence of discourse connectives. To overcome this issue, we design an end-to-end neural model to explicitly generate discourse connectives for …
Implicit Discourse Relation ClassificationRelationRelation ClassificationTransfer and Active Learning for Dissonance Detection: Addressing the Rare-Class Challenge
While transformer-based systems have enabled greater accuracies with fewer training examples, data acquisition obstacles still persist for rare-class tasks -- when the class label is very infrequent (e.g. < 5% of samples…
Active LearningImplicit Discourse Relation ClassificationTransfer LearningPre-trained Sentence Embeddings for Implicit Discourse Relation Classification
Implicit discourse relations bind smaller linguistic units into coherent texts. Automatic sense prediction for implicit relations is hard, because it requires understanding the semantics of the linked arguments. Furtherm…
ClassificationImplicit Discourse Relation ClassificationImplicit RelationsRelation+3Label distributions help implicit discourse relation classification
Implicit discourse relations can convey more than one relation sense, but much of the research on discourse relations has focused on single relation senses. Recently, DiscoGeM, a novel multi-domain corpus, which contains…
ClassificationImplicit Discourse Relation ClassificationRelationRelation ClassificationCVAE-based Re-anchoring for Implicit Discourse Relation Classification
Training implicit discourse relation classifiers suffers from data sparsity. Variational AutoEncoder (VAE) appears to be the proper solution. It is because ideally VAE is capable of generating inexhaustible varying sampl…
Binary ClassificationClassificationData AugmentationImplicit Discourse Relation Classification+3Entity Enhancement for Implicit Discourse Relation Classification in the Biomedical Domain
Implicit discourse relation classification is a challenging task, in particular when the text domain is different from the standard Penn Discourse Treebank (PDTB; Prasad et al., 2008) training corpus domain (Wall Street …
Implicit Discourse Relation ClassificationRelationRelation ClassificationLet’s be explicit about that: Distant supervision for implicit discourse relation classification via connective prediction
In implicit discourse relation classification, we want to predict the relation between adjacent sentences in the absence of any overt discourse connectives. This is challenging even for humans, leading to shortage of ann…
ClassificationImplicit Discourse Relation ClassificationImplicit RelationsLanguage Modeling+4Let's be explicit about that: Distant supervision for implicit discourse relation classification via connective prediction
In implicit discourse relation classification, we want to predict the relation between adjacent sentences in the absence of any overt discourse connectives. This is challenging even for humans, leading to shortage of ann…
ClassificationImplicit Discourse Relation ClassificationImplicit RelationsLanguage Modeling+4Using a Penalty-based Loss Re-estimation Method to Improve Implicit Discourse Relation Classification
We tackle implicit discourse relation classification, a task of automatically determining semantic relationships between arguments. The attention-worthy words in arguments are crucial clues for classifying the discourse …
Implicit Discourse Relation ClassificationRelationRelation ClassificationImplicit Discourse Relation Classification: We Need to Talk about Evaluation
Implicit relation classification on Penn Discourse TreeBank (PDTB) 2.0 is a common benchmark task for evaluating the understanding of discourse relations. However, the lack of consistency in preprocessing and evaluation …
ClassificationGeneral ClassificationImplicit Discourse Relation ClassificationRelation+2Adapting BERT to Implicit Discourse Relation Classification with a Focus on Discourse Connectives
BERT, a neural network-based language model pre-trained on large corpora, is a breakthrough in natural language processing, significantly outperforming previous state-of-the-art models in numerous tasks. However, there h…
General ClassificationImplicit Discourse Relation ClassificationLanguage ModelingLanguage Modelling+3On the Importance of Word and Sentence Representation Learning in Implicit Discourse Relation Classification
Implicit discourse relation classification is one of the most difficult parts in shallow discourse parsing as the relation prediction without explicit connectives requires the language understanding at both the text span…
Discourse ParsingGeneral ClassificationImplicit Discourse Relation ClassificationRelation+4Unsupervised Adversarial Domain Adaptation for Implicit Discourse Relation Classification
Implicit discourse relations are not only more challenging to classify, but also to annotate, than their explicit counterparts. We tackle situations where training data for implicit relations are lacking, and exploit dom…
ClassificationDomain AdaptationGeneral ClassificationImplicit Discourse Relation Classification+4Next Sentence Prediction helps Implicit Discourse Relation Classification within and across Domains
Implicit discourse relation classification is one of the most difficult tasks in discourse parsing. Previous studies have generally focused on extracting better representations of the relational arguments. In order to so…
Discourse ParsingGeneral ClassificationImplicit Discourse Relation ClassificationRelation+2Semantic Graph Convolutional Network for Implicit Discourse Relation Classification
Implicit discourse relation classification is of great importance for discourse parsing, but remains a challenging problem due to the absence of explicit discourse connectives communicating these relations. Modeling the …
ClassificationDiscourse ParsingGeneral ClassificationImplicit Discourse Relation Classification+2Zero-shot transfer for implicit discourse relation classification
Automatically classifying the relation between sentences in a discourse is a challenging task, in particular when there is no overt expression of the relation. It becomes even more challenging by the fact that annotated …
ClassificationGeneral ClassificationImplicit Discourse Relation ClassificationRelation+2Zero-shot transfer for implicit discourse relation classification
Automatically classifying the relation between sentences in a discourse is a challenging task, in particular when there is no overt expression of the relation. It becomes even more challenging by the fact that annotated …
ClassificationGeneral ClassificationImplicit Discourse Relation ClassificationRelation+2