# The CLEF-2025 CheckThat! Lab: Subjectivity, Fact-Checking, Claim Normalization, and Retrieval

arXiv: https://arxiv.org/abs/2503.14828 · HTML: https://mlsanity.com/paper/2503.14828/

## Key facts

- Cited by 14 papers in the map (data through 14 Oct 2026).
- Builds on 31 of its 53 references that are in the map.
- First posted on arXiv 19 Mar 2025.

## Builds on (most cited first, 30 of 31)

- [FEVER: a large-scale dataset for Fact Extraction and VERification](https://mlsanity.com/paper/1803.05355/) (2018)
- [Fact or Fiction: Verifying Scientific Claims](https://mlsanity.com/paper/2004.14974/) (2020)
- [A Survey on Automated Fact-Checking](https://mlsanity.com/paper/2108.11896/) (2021)
- [CORD-19: The COVID-19 Open Research Dataset](https://mlsanity.com/paper/2004.10706/) (2020)
- [MultiFC: A Real-World Multi-Domain Dataset for Evidence-Based Fact Checking of Claims](https://mlsanity.com/paper/1909.03242/) (2019)
- [Automated Fact-Checking for Assisting Human Fact-Checkers](https://mlsanity.com/paper/2103.07769/) (2021)
- [AVeriTeC: A Dataset for Real-world Claim Verification with Evidence from the Web](https://mlsanity.com/paper/2305.13117/) (2023)
- [SemEval-2020 Task 11: Detection of Propaganda Techniques in News Articles](https://mlsanity.com/paper/2009.02696/) (2020)
- [SemEval-2017 Task 8: RumourEval: Determining rumour veracity and support for rumours](https://mlsanity.com/paper/1704.05972/) (2017)
- [RumourEval 2019: Determining Rumour Veracity and Support for Rumours](https://mlsanity.com/paper/1809.06683/) (2018)
- [Fighting the COVID-19 Infodemic: Modeling the Perspective of Journalists, Fact-Checkers, Social Media Platforms, Policy Makers, and the Society](https://mlsanity.com/paper/2005.00033/) (2020)
- [SemEval-2021 Task 6: Detection of Persuasion Techniques in Texts and Images](https://mlsanity.com/paper/2105.09284/) (2021)
- [A Retrospective Analysis of the Fake News Challenge Stance Detection Task](https://mlsanity.com/paper/1806.05180/) (2018)
- [GERE: Generative Evidence Retrieval for Fact Verification](https://mlsanity.com/paper/2204.05511/) (2022)
- [QuanTemp: A real-world open-domain benchmark for fact-checking numerical claims](https://mlsanity.com/paper/2403.17169/) (2024)
- [ArAIEval Shared Task: Persuasion Techniques and Disinformation Detection in Arabic Text](https://mlsanity.com/paper/2311.03179/) (2023)
- [SemEval-2019 Task 8: Fact Checking in Community Question Answering Forums](https://mlsanity.com/paper/1906.01727/) (2019)
- [From Chaos to Clarity: Claim Normalization to Empower Fact-Checking](https://mlsanity.com/paper/2310.14338/) (2023)
- [FactCheck Editor: Multilingual Text Editor with End-to-End fact-checking](https://mlsanity.com/paper/2404.19482/) (2024)
- [ArAIEval Shared Task: Propagandistic Techniques Detection in Unimodal and Multimodal Arabic Content](https://mlsanity.com/paper/2407.04247/) (2024)
- [Automated Content Moderation Increases Adherence to Community Guidelines](https://mlsanity.com/paper/2210.10454/) (2022)
- [What Makes Medical Claims (Un)Verifiable? Analyzing Entity and Relation Properties for Fact Verification](https://mlsanity.com/paper/2402.01360/) (2024)
- [Multimodal Fact-Checking with Vision Language Models: A Probing Classifier based Solution with Embedding Strategies](https://mlsanity.com/paper/2412.05155/) (2024)
- [SciTweets -- A Dataset and Annotation Framework for Detecting Scientific Online Discourse](https://mlsanity.com/paper/2206.07360/) (2022)
- [SubjECTive-QA: Measuring Subjectivity in Earnings Call Transcripts' QA Through Six-Dimensional Feature Analysis](https://mlsanity.com/paper/2410.20651/) (2024)
- [Findings of Factify 2: Multimodal Fake News Detection](https://mlsanity.com/paper/2307.10475/) (2023)
- [MM-Claims: A Dataset for Multimodal Claim Detection in Social Media](https://mlsanity.com/paper/2205.01989/) (2022)
- [An Entity-based Claim Extraction Pipeline for Real-world Biomedical Fact-checking](https://mlsanity.com/paper/2304.05268/) (2023)
- [Overview of the CLAIMSCAN-2023: Uncovering Truth in Social Media through Claim Detection and Identification of Claim Spans](https://mlsanity.com/paper/2310.19267/) (2023)
- [Numerical Claim Detection in Finance: A New Financial Dataset, Weak-Supervision Model, and Market Analysis](https://mlsanity.com/paper/2402.11728/) (2024)

## Built on by (most cited first, 14 of 14)

- [DS@GT at CheckThat! 2025: Evaluating Context and Tokenization Strategies for Numerical Fact Verification](https://mlsanity.com/paper/2507.06195/) (2025)
- [Deep Retrieval at CheckThat! 2025: Identifying Scientific Papers from Implicit Social Media Mentions via Hybrid Retrieval and Re-Ranking](https://mlsanity.com/paper/2505.23250/) (2025)
- [CEA-LIST at CheckThat! 2025: Evaluating LLMs as Detectors of Bias and Opinion in Text](https://mlsanity.com/paper/2507.07539/) (2025)
- [AIRwaves at CheckThat! 2025: Retrieving Scientific Sources for Implicit Claims on Social Media with Dual Encoders and Neural Re-Ranking](https://mlsanity.com/paper/2509.19509/) (2025)
- [DS@GT at CheckThat! 2025: Detecting Subjectivity via Transfer-Learning and Corrective Data Augmentation](https://mlsanity.com/paper/2507.06189/) (2025)
- [AI Wizards at CheckThat! 2025: Enhancing Transformer-Based Embeddings with Sentiment for Subjectivity Detection in News Articles](https://mlsanity.com/paper/2507.11764/) (2025)
- [QU-NLP at CheckThat! 2025: Multilingual Subjectivity in News Articles Detection using Feature-Augmented Transformer Models with Sequential Cross-Lingual Fine-Tuning](https://mlsanity.com/paper/2507.21095/) (2025)
- [TurQUaz at CheckThat! 2025: Debating Large Language Models for Scientific Web Discourse Detection](https://mlsanity.com/paper/2508.08265/) (2025)
- [DS@GT at CheckThat! 2025: A Simple Retrieval-First, LLM-Backed Framework for Claim Normalization](https://mlsanity.com/paper/2508.17402/) (2025)
- [AKCIT-FN at CheckThat! 2025: Switching Fine-Tuned SLMs and LLM Prompting for Multilingual Claim Normalization](https://mlsanity.com/paper/2509.11496/) (2025)
- [XplaiNLP at CheckThat! 2025: Multilingual Subjectivity Detection with Finetuned Transformers and Prompt-Based Inference with Large Language Models](https://mlsanity.com/paper/2509.12130/) (2025)
- [Reasoning-Guided Claim Normalization for Noisy Multilingual Social Media Posts](https://mlsanity.com/paper/2511.05078/) (2025)
- [Not All Subjectivity Is the Same! Defining Desiderata for the Evaluation of Subjectivity in NLP](https://mlsanity.com/paper/2603.28351/) (2026)
- [Relational Linear Properties in Language Models: An Empirical Investigation](https://mlsanity.com/paper/2605.22532/) (2026)

## Abstract (arXiv)

The CheckThat! lab aims to advance the development of innovative technologies designed to identify and counteract online disinformation and manipulation efforts across various languages and platforms. The first five editions focused on key tasks in the information verification pipeline, including check-worthiness, evidence retrieval and pairing, and verification. Since the 2023 edition, the lab has expanded its scope to address auxiliary tasks that support research and decision-making in verification. In the 2025 edition, the lab revisits core verification tasks while also considering auxiliary challenges. Task 1 focuses on the identification of subjectivity (a follow-up from CheckThat! 2024), Task 2 addresses claim normalization, Task 3 targets fact-checking numerical claims, and Task 4 explores scientific web discourse processing. These tasks present challenging classification and retrieval problems at both the document and span levels, including multilingual settings.