HerO at AVeriTeC: The Herd of Open Large Language Models for Verifying Real-World Claims
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Abstract (arXiv)
To tackle the AVeriTeC shared task hosted by the FEVER-24, we introduce a system that only employs publicly available large language models (LLMs) for each step of automated fact-checking, dubbed the Herd of Open LLMs for verifying real-world claims (HerO). For evidence retrieval, a language model is used to enhance a query by generating hypothetical fact-checking documents. We prompt pretrained and fine-tuned LLMs for question generation and veracity prediction by crafting prompts with retrieved in-context samples. HerO achieved 2nd place on the leaderboard with the AVeriTeC score of 0.57, suggesting the potential of open LLMs for verifying real-world claims. For future research, we make our code publicly available at https://github.com/ssu-humane/HerO.
Key facts. Cited by 12 papers in the map (data through 14 Oct 2026). Builds on 14 of its 23 references that are in the map. First posted on arXiv 16 Oct 2024.
Builds on
14 of 23 references.
References · 14
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- 2024The Llama 3 Herd of Modelscited by 14,715
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- 2022Precise Zero-Shot Dense Retrieval without Relevance Labelscited by 517
- 2021A Survey on Automated Fact-Checkingcited by 378
- 2017"Liar, Liar Pants on Fire": A New Benchmark Dataset for Fake News Detectioncited by 363
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2 more
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Citing papers per year: 2025: 7; 2026: 5.
12 papers.
- 2025Debating Truth: Debate-driven Claim Verification with Multiple Large Language Model Agentscited by 6
- 2025Team HUMANE at AVeriTeC 2025: HerO 2 for Efficient Fact Verificationcited by 4
- 2025Fact2Fiction: Targeted Poisoning Attack to Agentic Fact-checking Systemcited by 4
- 2025Attacks by Content: Automated Fact-checking is an AI Security Issuecited by 4
- 2025AIC CTU@FEVER 8: On-premise fact checking through long context RAGcited by 3
- 2026Multi-Sourced, Multi-Agent Evidence Retrieval for Fact-Checkingcited by 3
- 2026The Automatic Verification of Image-Text Claims (AVerImaTeC) Shared Taskcited by 2
- 2026From Verdict to Process: Agentic Reinforcement Learning for Multi-Stage Fact Verificationcited by 1
- 2025PledgeTracker: A System for Monitoring the Fulfilment of Pledgescited by 0
- 2025ClaimCheck: Real-Time Fact-Checking with Small Language Modelscited by 0
- 2026VILLAIN at AVerImaTeC: Verifying Image-Text Claims via Multi-Agent Collaborationcited by 0
- 2026CAAFC: Chronological Actionable Automated Fact-Checker for misinformation / non-factual hallucination detection and correctioncited by 0
- 2026From Verdict to Process: Agentic Reinforcement Learning for Multi-Stage Fact Verification11 Jun 2026
- 2026CAAFC: Chronological Actionable Automated Fact-Checker for misinformation / non-factual hallucination detection and correction12 May 2026
- 2026Multi-Sourced, Multi-Agent Evidence Retrieval for Fact-Checking27 Feb 2026
- 2026The Automatic Verification of Image-Text Claims (AVerImaTeC) Shared Task11 Feb 2026
- 2026VILLAIN at AVerImaTeC: Verifying Image-Text Claims via Multi-Agent Collaboration4 Feb 2026
- 2025Attacks by Content: Automated Fact-checking is an AI Security Issue13 Oct 2025
- 2025ClaimCheck: Real-Time Fact-Checking with Small Language Models22 Sep 2025
- 2025PledgeTracker: A System for Monitoring the Fulfilment of Pledges15 Sep 2025
- 2025Fact2Fiction: Targeted Poisoning Attack to Agentic Fact-checking System8 Aug 2025
- 2025AIC CTU@FEVER 8: On-premise fact checking through long context RAG5 Aug 2025
- 2025Debating Truth: Debate-driven Claim Verification with Multiple Large Language Model Agents25 Jul 2025
- 2025Team HUMANE at AVeriTeC 2025: HerO 2 for Efficient Fact Verification15 Jul 2025