Search Results for author: Arnav Arora

Found 4 papers, 1 papers with code

Few-Shot Cross-Lingual Stance Detection with Sentiment-Based Pre-Training

no code implementations13 Sep 2021 Momchil Hardalov, Arnav Arora, Preslav Nakov, Isabelle Augenstein

Most research in stance detection, however, has been limited to working with a single language and on a few limited targets, with little work on cross-lingual stance detection.

Stance Detection

Cross-Domain Label-Adaptive Stance Detection

no code implementations15 Apr 2021 Momchil Hardalov, Arnav Arora, Preslav Nakov, Isabelle Augenstein

In this paper, we perform an in-depth analysis of 16 stance detection datasets, and we explore the possibility for cross-domain learning from them.

Domain Adaptation Stance Detection

A Survey on Stance Detection for Mis- and Disinformation Identification

no code implementations27 Feb 2021 Momchil Hardalov, Arnav Arora, Preslav Nakov, Isabelle Augenstein

Detecting attitudes expressed in texts, also known as stance detection, has become an important task for the detection of false information online, be it misinformation (unintentionally false) or disinformation (intentionally false, spread deliberately with malicious intent).

Fact Checking Misinformation +3

Multi-Hop Fact Checking of Political Claims

1 code implementation10 Sep 2020 Wojciech Ostrowski, Arnav Arora, Pepa Atanasova, Isabelle Augenstein

We: 1) construct a small annotated dataset, PolitiHop, of evidence sentences for claim verification; 2) compare it to existing multi-hop datasets; and 3) study how to transfer knowledge from more extensive in- and out-of-domain resources to PolitiHop.

Fact Checking Transfer Learning

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