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Found 16 papers, 3 papers with code
Subtitles to Segmentation: Improving Low-Resource Speech-to-TextTranslation Pipelines
In this work, we focus on improving ASR output segmentation in the context of low-resource language speech-to-text translation.
AMPERSAND: Argument Mining for PERSuAsive oNline Discussions
Our approach for relation prediction uses contextual information in terms of fine-tuning a pre-trained language model and leveraging discourse relations based on Rhetorical Structure Theory.
Detecting and Reducing Bias in a High Stakes Domain
Gang-involved youth in cities such as Chicago sometimes post on social media to express their aggression towards rival gangs and previous research has demonstrated that a deep learning approach can predict aggression and loss in posts.
Neural Network Alignment for Sentential Paraphrases
We present a monolingual alignment system for long, sentence- or clause-level alignments, and demonstrate that systems designed for word- or short phrase-based alignment are ill-suited for these longer alignments.
A Robust Abstractive System for Cross-Lingual Summarization
We present a robust neural abstractive summarization system for cross-lingual summarization.
Fixed That for You: Generating Contrastive Claims with Semantic Edits
Understanding contrastive opinions is a key component of argument generation.
Identifying therapist conversational actions across diverse psychotherapeutic approaches
We propose to apply dialogue act classification to therapy transcripts, using a therapy-specific labeling scheme, in order to gain a high-level understanding of the flow of conversation in therapy sessions.
Analyzing the Semantic Types of Claims and Premises in an Online Persuasive Forum
Argumentative text has been analyzed both theoretically and computationally in terms of argumentative structure that consists of argument components (e. g., claims, premises) and their argumentative relations (e. g., support, attack).
Crowd-Sourced Iterative Annotation for Narrative Summarization Corpora
We present an iterative annotation process for producing aligned, parallel corpora of abstractive and extractive summaries for narrative.
Towards Automatic Detection of Narrative Structure
Using this corpus, we explore the correspondence between LabovÂ’s elements of narrative structure and the implicit discourse relations of the Penn Discourse Treebank, and we construct a mapping between the elements of narrative structure and the discourse relation classes of the PDTB.
