no code implementations • ACL (NLP4PosImpact) 2021 • Pooneh Mousavi, Jessica Ouyang
Social media has changed the way we engage in social activities.
no code implementations • EACL (WASSA) 2021 • Soumya Sourav, Jessica Ouyang
Human language encompasses more than just text; it also conveys emotions through tone and gestures.
no code implementations • 24 Apr 2024 • Xiangci Li, Sihao Chen, Rajvi Kapadia, Jessica Ouyang, Fan Zhang
Claim verification in real-world settings (e. g. against a large collection of candidate evidences retrieved from the web) typically requires identifying and aggregating a complete set of evidence pieces that collectively provide full support to the claim.
no code implementations • 17 Apr 2024 • Xiangci Li, Jessica Ouyang
To convince readers of the novelty of their research paper, authors must perform a literature review and compose a coherent story that connects and relates prior works to the current work.
1 code implementation • 6 Mar 2024 • Xiangci Li, Linfeng Song, Lifeng Jin, Haitao Mi, Jessica Ouyang, Dong Yu
In this paper, we present a high-quality benchmark named multi-source Wizard of Wikipedia (Ms. WoW) for evaluating multi-source dialogue knowledge selection and response generation.
no code implementations • 28 Feb 2024 • Biswadip Mandal, Xiangci Li, Jessica Ouyang
Abstractive citation text generation is usually framed as an infilling task, where a sequence-to-sequence model is trained to generate a citation given a reference paper and the context window around the target; the generated citation should be a brief discussion of the reference paper as it relates to the citing context.
no code implementations • 20 Feb 2024 • Xiangci Li, Jessica Ouyang
Due to the rapid pace of research publications, keeping up to date with all the latest related papers is very time-consuming, even with daily feed tools.
1 code implementation • 12 Sep 2023 • Xiangci Li, Yi-Hui Lee, Jessica Ouyang
Because manual CTS annotation is extremely time- and labor-intensive, we experiment with distant labeling of candidate CTS sentences, achieving sufficiently strong performance to substitute for expensive human annotations in model training, and we propose a human-in-the-loop, keyword-based CTS retrieval approach that makes generating citation texts grounded in the full text of cited papers both promising and practical.
1 code implementation • NAACL 2022 • Xiangci Li, Biswadip Mandal, Jessica Ouyang
As a first step toward a linguistically-motivated related work generation framework, we present a Citation Oriented Related Work Annotation (CORWA) dataset that labels different types of citation text fragments from different information sources.
no code implementations • 6 Jan 2022 • Xiangci Li, Jessica Ouyang
In this survey, we conduct a meta-study to compare the existing literature on related work generation from the perspectives of problem formulation, dataset collection, methodological approach, performance evaluation, and future prospects to provide the reader insight into the progress of the state-of-the-art studies, as well as and how future studies can be conducted.
no code implementations • ACL 2019 • Jessica Ouyang, Kathy Mckeown
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.
no code implementations • NAACL 2019 • Jessica Ouyang, Boya Song, Kathy Mckeown
We present a robust neural abstractive summarization system for cross-lingual summarization.
no code implementations • EACL 2017 • Jessica Ouyang, Serina Chang, Kathy Mckeown
We present an iterative annotation process for producing aligned, parallel corpora of abstractive and extractive summaries for narrative.
no code implementations • LREC 2014 • Jessica Ouyang, Kathy Mckeown
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.