70 citations · 134 across the 9 of their papers we have counts for
13 papers
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…
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…
State-of-the-art generalisation research in NLP: A taxonomy and review
Dieuwke Hupkes, Mario Giulianelli, Verna Dankers +17
The ability to generalise well is one of the primary desiderata of natural language processing (NLP). Yet, what 'good generalisation' entails and how it should be evaluated is not…
ReFinED: An Efficient Zero-shot-capable Approach to End-to-End Entity Linking
Tom Ayoola, Shubhi Tyagi, Joseph Fisher +2
We introduce ReFinED, an efficient end-to-end entity linking model which uses fine-grained entity types and entity descriptions to perform linking. The model performs mention detec…
Robust Information Retrieval for False Claims with Distracting Entities In Fact Extraction and Verification
Mingwen Dong, Christos Christodoulopoulos, Sheng-Min Shih +1
Accurate evidence retrieval is essential for automated fact checking. Little previous research has focused on the differences between true and false claims and how they affect evid…
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…
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…
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…
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…
Simple Large-scale Relation Extraction from Unstructured Text
Christos Christodoulopoulos, Arpit Mittal
Knowledge-based question answering relies on the availability of facts, the majority of which cannot be found in structured sources (e.g. Wikipedia info-boxes, Wikidata). One of th…
FEVER: a large-scale dataset for Fact Extraction and VERification
James Thorne, Andreas Vlachos, Christos Christodoulopoulos +1
In this paper we introduce a new publicly available dataset for verification against textual sources, FEVER: Fact Extraction and VERification. It consists of 185,445 claims generat…
Relational Learning and Feature Extraction by Querying over Heterogeneous Information Networks
Parisa Kordjamshidi, Sameer Singh, Daniel Khashabi +4
Many real world systems need to operate on heterogeneous information networks that consist of numerous interacting components of different types. Examples include systems that perf…
Transliteration in Any Language with Surrogate Languages
Stephen Mayhew, Christos Christodoulopoulos, Dan Roth
We introduce a method for transliteration generation that can produce transliterations in every language. Where previous results are only as multilingual as Wikipedia, we show how…