mlsanityData to 7 Oct 2026

Multimedia Verification Through Multi-Agent Deep Research Multimodal Large Language Models

arXiv 2507.04410 ↗First posted 6 Jul 2025cs.CV cs.AI cs.IRcited by 4

On the map: Multimodal LLMs / vision-language models → MLLM jailbreaks and adversarial robustness

also in 1 more
Abstract (arXiv)

This paper presents our submission to the ACMMM25 - Grand Challenge on Multimedia Verification. We developed a multi-agent verification system that combines Multimodal Large Language Models (MLLMs) with specialized verification tools to detect multimedia misinformation. Our system operates through six stages: raw data processing, planning, information extraction, deep research, evidence collection, and report generation. The core Deep Researcher Agent employs four tools: reverse image search, metadata analysis, fact-checking databases, and verified news processing that extracts spatial, temporal, attribution, and motivational context. We demonstrate our approach on a challenge dataset sample involving complex multimedia content. Our system successfully verified content authenticity, extracted precise geolocation and timing information, and traced source attribution across multiple platforms, effectively addressing real-world multimedia verification scenarios.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Placed in MLLM jailbreaks and adversarial robustness, one of 16 directions in Multimodal LLMs / vision-language models. Builds on 11 of its 33 references that are in the map. First posted on arXiv 6 Jul 2025.

Builds on

11 of 33 references.

References · 11

  1. 2019FaceForensics++: Learning to Detect Manipulated Facial Imagescited by 1,095
  2. 2024V-DPO: Mitigating Hallucination in Large Vision Language Models via Vision-Guided Direct Preference Optimizationcited by 67
  3. 2024Can LLMs Produce Faithful Explanations For Fact-checking? Towards Faithful Explainable Fact-Checking via Multi-Agent Debatecited by 48
  4. 2024DEFAME: Dynamic Evidence-based FAct-checking with Multimodal Expertscited by 42
  5. 2024FKA-Owl: Advancing Multimodal Fake News Detection through Knowledge-Augmented LVLMscited by 38
  6. 2024Logical Consistency of Large Language Models in Fact-checkingcited by 15
  7. 2024LangXAI: Integrating Large Vision Models for Generating Textual Explanations to Enhance Explainability in Visual Perception Taskscited by 12
  8. 2025Heart2Mind: Human-Centered Contestable Psychiatric Disorder Diagnosis System using Wearable ECG Monitorscited by 4
  9. 2025Evidence-Grounded Multimodal Misinformation Detection with Attention-Based GNNscited by 2
  10. 2016PicHunt: Social Media Image Retrieval for Improved Law Enforcementcited by 1
  11. 2025E-FreeM2: Efficient Training-Free Multi-Scale and Cross-Modal News Verification via MLLMscited by 1

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 4.

4 papers.

  1. 2026Contestable Multi-Agent Debate with Arena-based Argumentative Computation for Multimedia Verificationcited by 2
  2. 2026Consensus-based Agentic Large Language Model Framework for Harmonized Tariff Schedule Code Classificationcited by 0
  3. 2026TUE-Detector: A Tool-Using Expert MLLM-Based Detector for AI-Generated Videoscited by 0
  4. 2026Self-Evolving Multimedia Verification through Memory Consolidation of Contestation Experiencescited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025RAMA: Retrieval-Augmented Multi-Agent Framework for Misinformation Detection in Multimodal Fact-Checking
  2. 2026Can Multimodal Large Language Models Generate and Detect Multimodal Social Media Fake News?
  3. 2026ReMMD: Realistic Multilingual Multi-Image Agentic Verification for Multimodal Misinformation Detection
  4. 2026Fact or Fake? Assessing the Role of Deepfake Detectors in Multimodal Misinformation Detection
  5. 2024Multimodal Large Language Models to Support Real-World Fact-Checking
  6. 2025Debunk and Infer: Multimodal Fake News Detection via Diffusion-Generated Evidence and LLM Reasoning
  7. 2026FactGuard: Agentic Video Misinformation Detection via Reinforcement Learning
  8. 2026Agentic Mixed-Source Multi-Modal Misinformation Detection with Adaptive Test-Time Scaling