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Found 16 papers, 3 papers with code
Improving Neural Machine Translation with the Abstract Meaning Representation by Combining Graph and Sequence Transformers
Previous studies have shown that the Abstract Meaning Representation (AMR) can improve Neural Machine Translation (NMT).
Dependency Dialogue Acts -- Annotation Scheme and Case Study
DDA combines and adapts features from existing dialogue annotation frameworks, and emphasizes the multi-relational response structure of dialogues in addition to the dialogue acts and rhetorical relations.
Automatic Identification of Motivation for Code-Switching in Speech Transcripts
We build the first system (to our knowledge) to automatically identify a wide range of motivations that speakers code-switch in everyday speech, achieving an accuracy of 75% across all motivations.
Forming Trees with Treeformers
Popular models such as Transformers and LSTMs use tokens as its unit of information.
DocAMR: Multi-Sentence AMR Representation and Evaluation
Despite extensive research on parsing of English sentences into Abstraction Meaning Representation (AMR) graphs, which are compared to gold graphs via the Smatch metric, full-document parsing into a unified graph representation lacks well-defined representation and evaluation.
Avoiding Overlap in Data Augmentation for AMR-to-Text Generation
We propose methods for excluding parts of Gigaword to remove this overlap, and show that our approach leads to a more realistic evaluation of the task of AMR-to-text generation.
ASQ: Automatically Generating Question-Answer Pairs using AMRs
We introduce ASQ, a tool to automatically mine questions and answers from a sentence using the Abstract Meaning Representation (AMR).
Athena: Constructing Dialogues Dynamically with Discourse Constraints
This report describes Athena, a dialogue system for spoken conversation on popular topics and current events.
The Materials Science Procedural Text Corpus: Annotating Materials Synthesis Procedures with Shallow Semantic Structures
Materials science literature contains millions of materials synthesis procedures described in unstructured natural language text.
Toward Abstractive Summarization Using Semantic Representations
We present a novel abstractive summarization framework that draws on the recent development of a treebank for the Abstract Meaning Representation (AMR).
