1 code implementation • ACL 2022 • Mounica Maddela, Mayank Kulkarni, Daniel Preotiuc-Pietro
Controllable summarization aims to provide summaries that take into account user-specified aspects and preferences to better assist them with their information need, as opposed to the standard summarization setup which build a single generic summary of a document. We introduce a human-annotated data set EntSUM for controllable summarization with a focus on named entities as the aspects to control. We conduct an extensive quantitative analysis to motivate the task of entity-centric summarization and show that existing methods for controllable summarization fail to generate entity-centric summaries.
no code implementations • 14 Sep 2023 • Rajarshi Bhowmik, Marco Ponza, Atharva Tendle, Anant Gupta, Rebecca Jiang, Xingyu Lu, Qian Zhao, Daniel Preotiuc-Pietro
In text documents such as news articles, the content and key events usually revolve around a subset of all the entities mentioned in a document.
1 code implementation • 13 Sep 2023 • Niklas Stoehr, Pengxiang Cheng, Jing Wang, Daniel Preotiuc-Pietro, Rajarshi Bhowmik
We compare pairwise, pointwise and listwise prompting techniques to elicit a language model's ranking knowledge.
no code implementations • 25 May 2023 • Genta Indra Winata, Lingjue Xie, Karthik Radhakrishnan, Shijie Wu, Xisen Jin, Pengxiang Cheng, Mayank Kulkarni, Daniel Preotiuc-Pietro
Real-life multilingual systems should be able to efficiently incorporate new languages as data distributions fed to the system evolve and shift over time.
1 code implementation • 19 Dec 2022 • Xisen Jin, Xiang Ren, Daniel Preotiuc-Pietro, Pengxiang Cheng
In this paper, we study the problem of merging individual models built on different training data sets to obtain a single model that performs well both across all data set domains and can generalize on out-of-domain data.
1 code implementation • 5 Apr 2022 • Mounica Maddela, Mayank Kulkarni, Daniel Preotiuc-Pietro
Our analysis and results show the challenging nature of this task and of the proposed data set.
no code implementations • EACL 2021 • Ravneet Arora, Chen-Tse Tsai, Daniel Preotiuc-Pietro
However, the typical experimental setup for evaluating Named Entity Recognition (NER) systems is not directly applicable to systems that process text in real time as the text is being typed.
no code implementations • COLING 2020 • Tariq Alhindi, Smaranda Muresan, Daniel Preotiuc-Pietro
A 2018 study led by the Media Insight Project showed that most journalists think that a clearmarking of what is news reporting and what is commentary or opinion (e. g., editorial, op-ed)is essential for gaining public trust.
no code implementations • ACL 2020 • Shruti Rijhwani, Daniel Preotiuc-Pietro
Natural language processing models often have to make predictions on text data that evolves over time as a result of changes in language use or the information described in the text.
no code implementations • ACL 2020 • Jing Wang, Mayank Kulkarni, Daniel Preotiuc-Pietro
Named entity recognition is a key component of many text processing pipelines and it is thus essential for this component to be robust to different types of input.
no code implementations • ACL 2020 • Antonis Maronikolakis, Danae Sanchez Villegas, Daniel Preotiuc-Pietro, Nikolaos Aletras
Parody is a figurative device used to imitate an entity for comedic or critical purposes and represents a widespread phenomenon in social media through many popular parody accounts.
1 code implementation • ACL 2019 • Daniel Preotiuc-Pietro, Mihaela Gaman, Nikolaos Aletras
Complaining is a basic speech act regularly used in human and computer mediated communication to express a negative mismatch between reality and expectations in a particular situation.