Papers Discourse Parsing
“Discourse Parsing” 태그가 달린 논문 195편 · 필터 해제
Beyond Supervised Clarification: Input Rewriting with LLMs for Dialogue Discourse Parsing
Rewriting inputs to improve frozen downstream models has become a common strategy in modern NLP pipelines. Prior work on incremental dialogue discourse parsing (DDP) shows that supervised clarification models can rewrite…
Discourse ParsingDraDDP: A Multimodal Multi-Party Dialogue Discourse Parsing Dataset
Multi-party dialogue discourse parsing aims to identify dependency structures and relation types between utterances in conversations. Previous studies are mostly limited to textual modality or two-party dialogue, failing…
Discourse ParsingNot Worth Mentioning? A Pilot Study on Salient Proposition Annotation
Despite a long tradition of work on extractive summarization, which by nature aims to recover the most important propositions in a text, little work has been done on operationalizing graded proposition salience in natura…
Discourse ParsingBeDiscovER: The Benchmark of Discourse Understanding in the Era of Reasoning Language Models
We introduce BeDiscovER (Benchmark of Discourse Understanding in the Era of Reasoning Language Models), an up-to-date, comprehensive suite for evaluating the discourse-level knowledge of modern LLMs. BeDiscovER compiles …
Temporal Relation ExtractionRelation ClassificationDiscourse ParsingBridging Discourse Treebanks with a Unified Rhetorical Structure Parser
We introduce UniRST, the first unified RST-style discourse parser capable of handling 18 treebanks in 11 languages without modifying their relation inventories. To overcome inventory incompatibilities, we propose and eva…
Relation ClassificationDiscourse ParsingAnnotate Rhetorical Relations with INCEpTION: A Comparison with Automatic Approaches
This research explores the annotation of rhetorical relations in discourse using the INCEpTION tool and compares manual annotation with automatic approaches based on large language models. The study focuses on sports rep…
Discourse ParsingCoMuMDR: Code-mixed Multi-modal Multi-domain corpus for Discourse paRsing in conversations
Discourse parsing is an important task useful for NLU applications such as summarization, machine comprehension, and emotion recognition. The current discourse parsing datasets based on conversations consists of written …
Discourse ParsingEmotion RecognitionReading ComprehensionESURF: Simple and Effective EDU Segmentation
Segmenting text into Elemental Discourse Units (EDUs) is a fundamental task in discourse parsing. We present a new simple method for identifying EDU boundaries, and hence segmenting them, based on lexical and character n…
Discourse ParsingAcquired TASTE: Multimodal Stance Detection with Textual and Structural Embeddings
Stance detection plays a pivotal role in enabling an extensive range of downstream applications, from discourse parsing to tracing the spread of fake news and the denial of scientific facts. While most stance classificat…
Discourse ParsingStance ClassificationStance DetectionGDTB: Genre Diverse Data for English Shallow Discourse Parsing across Modalities, Text Types, and Domains
Work on shallow discourse parsing in English has focused on the Wall Street Journal corpus, the only large-scale dataset for the language in the PDTB framework. However, the data is not openly available, is restricted to…
Discourse ParsingRelationRelation ClassificationBilingual Rhetorical Structure Parsing with Large Parallel Annotations
Discourse parsing is a crucial task in natural language processing that aims to reveal the higher-level relations in a text. Despite growing interest in cross-lingual discourse parsing, challenges persist due to limited …
Discourse ParsingEnd-to-End RST ParsingLlamipa: An Incremental Discourse Parser
This paper provides the first discourse parsing experiments with a large language model(LLM) finetuned on corpora annotated in the style of SDRT (Segmented Discourse Representation Theory Asher, 1993; Asher and Lascaride…
Discourse ParsingLanguage ModelingLanguage ModellingLarge Language ModelUnsupervised Mutual Learning of Dialogue Discourse Parsing and Topic Segmentation
The advancement of large language models (LLMs) has propelled the development of dialogue systems. Unlike the popular ChatGPT-like assistant model, which only satisfies the user's preferences, task-oriented dialogue syst…
Discourse ParsingGraph Neural NetworkTask-Oriented Dialogue SystemsCan we obtain significant success in RST discourse parsing by using Large Language Models?
Recently, decoder-only pre-trained large language models (LLMs), with several tens of billion parameters, have significantly impacted a wide range of natural language processing (NLP) tasks. While encoder-only or encoder…
DecoderDiscourse ParsingPrompt-based Logical Semantics Enhancement for Implicit Discourse Relation Recognition
Implicit Discourse Relation Recognition (IDRR), which infers discourse relations without the help of explicit connectives, is still a crucial and challenging task for discourse parsing. Recent works tend to exploit the h…
Discourse ParsingLanguage ModellingRelationSelf-Supervised LearningQUDEVAL: The Evaluation of Questions Under Discussion Discourse Parsing
Questions Under Discussion (QUD) is a versatile linguistic framework in which discourse progresses as continuously asking questions and answering them. Automatic parsing of a discourse to produce a QUD structure thus ent…
Discourse ParsingLanguage ModelingLanguage ModellingQuestion Generation+2What's Hard in English RST Parsing? Predictive Models for Error Analysis
Despite recent advances in Natural Language Processing (NLP), hierarchical discourse parsing in the framework of Rhetorical Structure Theory remains challenging, and our understanding of the reasons for this are as yet l…
Discourse ParsingRST-style Discourse Parsing Guided by Document-level Content Structures
Rhetorical Structure Theory based Discourse Parsing (RST-DP) explores how clauses, sentences, and large text spans compose a whole discourse and presents the rhetorical structure as a hierarchical tree. Existing RST pars…
Discourse ParsingSentenceA 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+3Structured Dialogue Discourse Parsing
Dialogue discourse parsing aims to uncover the internal structure of a multi-participant conversation by finding all the discourse~\emph{links} and corresponding~\emph{relations}. Previous work either treats this task as…
Discourse ParsingMultiple-choice