161 citations · 167 across the 4 of their papers we have counts for
8 papers · 1 filter
Few-Shot Data-to-Text Generation via Unified Representation and Multi-Source Learning
Alexander Hanbo Li, Mingyue Shang, Evangelia Spiliopoulou +9
We present a novel approach for structured data-to-text generation that addresses the limitations of existing methods that primarily focus on specific types of structured data. Our…
Textual Entailment for Event Argument Extraction: Zero- and Few-Shot with Multi-Source Learning
Oscar Sainz, Itziar Gonzalez-Dios, Oier Lopez de Lacalle +2
Recent work has shown that NLP tasks such as Relation Extraction (RE) can be recasted as Textual Entailment tasks using verbalizations, with strong performance in zero-shot and few…
ZS4IE: A toolkit for Zero-Shot Information Extraction with simple Verbalizations
Oscar Sainz, Haoling Qiu, Oier Lopez de Lacalle +2
The current workflow for Information Extraction (IE) analysts involves the definition of the entities/relations of interest and a training corpus with annotated examples. In this d…
FAMIE: A Fast Active Learning Framework for Multilingual Information Extraction
Minh Van Nguyen, Nghia Trung Ngo, Bonan Min +1
This paper presents FAMIE, a comprehensive and efficient active learning (AL) toolkit for multilingual information extraction. FAMIE is designed to address a fundamental problem in…
Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Survey
Bonan Min, Hayley Ross, Elior Sulem +6
Large, pre-trained transformer-based language models such as BERT have drastically changed the Natural Language Processing (NLP) field. We present a survey of recent work that uses…
ExcavatorCovid: Extracting Events and Relations from Text Corpora for Temporal and Causal Analysis for COVID-19
Bonan Min, Benjamin Rozonoyer, Haoling Qiu +2
Timely responses from policy makers to mitigate the impact of the COVID-19 pandemic rely on a comprehensive grasp of events, their causes, and their impacts. These events are repor…