activity
20172024
most citedFEVEROUS: Fact Extraction and VERification Over Unstructured and Structured information

52 citations · 54 across the 5 of their papers we have counts for

collaborators

9 papers

cs.CL2024

The Automated Verification of Textual Claims (AVeriTeC) Shared Task

Michael Schlichtkrull, Yulong Chen, Chenxi Whitehouse +9

The Automated Verification of Textual Claims (AVeriTeC) shared task asks participants to retrieve evidence and predict veracity for real-world claims checked by fact-checkers. Evid…

cs.CL2023

WebIE: Faithful and Robust Information Extraction on the Web

Chenxi Whitehouse, Clara Vania, Alham Fikri Aji +2

Extracting structured and grounded fact triples from raw text is a fundamental task in Information Extraction (IE). Existing IE datasets are typically collected from Wikipedia arti…

cs.CL202152 cited

FEVEROUS: Fact Extraction and VERification Over Unstructured and Structured information

Rami Aly, Zhijiang Guo, Michael Schlichtkrull +5

Fact verification has attracted a lot of attention in the machine learning and natural language processing communities, as it is one of the key methods for detecting misinformation…

cs.CL2021

Hidden Biases in Unreliable News Detection Datasets

Xiang Zhou, Heba Elfardy, Christos Christodoulopoulos +2

Automatic unreliable news detection is a research problem with great potential impact. Recently, several papers have shown promising results on large-scale news datasets with model…

cs.LG2019

Generating Token-Level Explanations for Natural Language Inference

James Thorne, Andreas Vlachos, Christos Christodoulopoulos +1

The task of Natural Language Inference (NLI) is widely modeled as supervised sentence pair classification. While there has been a lot of work recently on generating explanations of…

cs.CL2018

The Fact Extraction and VERification (FEVER) Shared Task

James Thorne, Andreas Vlachos, Oana Cocarascu +2

We present the results of the first Fact Extraction and VERification (FEVER) Shared Task. The task challenged participants to classify whether human-written factoid claims could be…