DetailVerifyBench supplies 1,000 images and densely annotated long captions to evaluate precise hallucination localization in multimodal large language models.
In Proceedings of the 31st International Conference on Computational Lin- guistics, pages 4186–4218, Abu Dhabi, UAE
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VLMs exhibit sharply higher counterfactual hallucination rates in Arabic and dialects despite high true-statement accuracy, revealed by the new M²CQA benchmark and CFHR metric.
V2E automates PoC generation, triggerability and profitability validation, and iterative refinement using LLMs to confirm exploitable smart contract vulnerabilities, outperforming baselines on 264 labeled contracts.
The survey organizes causes of hallucinations in MLLMs, reviews evaluation benchmarks and metrics, and outlines mitigation approaches plus open questions.
citing papers explorer
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DetailVerifyBench: A Benchmark for Dense Hallucination Localization in Long Image Captions
DetailVerifyBench supplies 1,000 images and densely annotated long captions to evaluate precise hallucination localization in multimodal large language models.
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Once Correct, Still Wrong: Counterfactual Hallucination in Multilingual Vision-Language Models
VLMs exhibit sharply higher counterfactual hallucination rates in Arabic and dialects despite high true-statement accuracy, revealed by the new M²CQA benchmark and CFHR metric.
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V2E: Validating Smart Contract Vulnerabilities through Profit-driven Exploit Generation and Execution
V2E automates PoC generation, triggerability and profitability validation, and iterative refinement using LLMs to confirm exploitable smart contract vulnerabilities, outperforming baselines on 264 labeled contracts.
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Hallucination of Multimodal Large Language Models: A Survey
The survey organizes causes of hallucinations in MLLMs, reviews evaluation benchmarks and metrics, and outlines mitigation approaches plus open questions.