SOTAVerified

Stance Detection

Stance detection is the extraction of a subject's reaction to a claim made by a primary actor. It is a core part of a set of approaches to fake news assessment.

Example:

  • Source: "Apples are the most delicious fruit in existence"
  • Reply: "Obviously not, because that is a reuben from Katz's"
  • Stance: deny

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1–10 of 343 papers

TitleStatusHype
Journalism-Guided Agentic In-Context Learning for News Stance Detection—0
LLMs are Introvert—0
MT2-CSD: A New Dataset and Multi-Semantic Knowledge Fusion Method for Conversational Stance Detection—0
Perspectives in Play: A Multi-Perspective Approach for More Inclusive NLP Systems—0
Abstract, Align, Predict: Zero-Shot Stance Detection via Cognitive Inductive Reasoning—0
PolitiSky24: U.S. Political Bluesky Dataset with User Stance Labels—0
Emotion-aware Dual Cross-Attentive Neural Network with Label Fusion for Stance Detection in Misinformative Social Media ContentCode0
What Media Frames Reveal About Stance: A Dataset and Study about Memes in Climate Change Discourse—0
Words That Unite The World: A Unified Framework for Deciphering Central Bank Communications GloballyCode1
Large Language Models Meet Stance Detection: A Survey of Tasks, Methods, Applications, Challenges and Future Directions—0
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All datasetsMGTABRumourEvalFNC-1ARC (AI2 Reasoning Challenge)argminDhoroniemergentiac1ibmcsmtsdPerspectrumpoldeb

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TESTEDF163.96—Unverified