Search Results for author: Jeffrey Flanigan

Found 16 papers, 3 papers with code

Dependency Dialogue Acts -- Annotation Scheme and Case Study

no code implementations25 Feb 2023 Jon Z. Cai, Brendan King, Margaret Perkoff, Shiran Dudy, Jie Cao, Marie Grace, Natalia Wojarnik, Ananya Ganesh, James H. Martin, Martha Palmer, Marilyn Walker, Jeffrey Flanigan

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

no code implementations30 Nov 2022 Ritu Belani, Jeffrey Flanigan

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

no code implementations14 Jul 2022 Nilay Patel, Jeffrey Flanigan

Popular models such as Transformers and LSTMs use tokens as its unit of information.

Abstractive Text Summarization Machine Translation +2

DocAMR: Multi-Sentence AMR Representation and Evaluation

1 code implementation NAACL 2022 Tahira Naseem, Austin Blodgett, Sadhana Kumaravel, Tim O'Gorman, Young-suk Lee, Jeffrey Flanigan, Ramón Fernandez Astudillo, Radu Florian, Salim Roukos, Nathan Schneider

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.

coreference-resolution Coreference Resolution

Avoiding Overlap in Data Augmentation for AMR-to-Text Generation

no code implementations ACL 2021 Wenchao Du, Jeffrey Flanigan

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.

AMR-to-Text Generation Data Augmentation +1

ASQ: Automatically Generating Question-Answer Pairs using AMRs

no code implementations20 May 2021 Geetanjali Rakshit, Jeffrey Flanigan

We introduce ASQ, a tool to automatically mine questions and answers from a sentence using the Abstract Meaning Representation (AMR).

Toward Abstractive Summarization Using Semantic Representations

1 code implementation HLT 2015 Fei Liu, Jeffrey Flanigan, Sam Thomson, Norman Sadeh, Noah A. Smith

We present a novel abstractive summarization framework that draws on the recent development of a treebank for the Abstract Meaning Representation (AMR).

Abstractive Text Summarization

Cannot find the paper you are looking for? You can Submit a new open access paper.