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over 2 years ago

Welcome to focus on our new paper in the field of Multimodal Hallucination: "Unified Hallucination Detection for Multimodal Large Language Models." 🤖💡 #AI #MultimodalAI #MachineLearning #NLP #LLMs #EasyDetect #Hallucination #UniHD 🔍 Our latest paper, "Unified Hallucination Detection for Multimodal Large Language Models," pioneers a unified approach, UniHD to detecting hallucinations in MLLMs (e.g., Text2Image & Image2Text) and introduces MHaluBench, a benchmark that spans diverse hallucination types and multimodal tasks. 📌ArXiv: https://t.co/4hz5js1ZZI 📌Home page: https://t.co/995guo3WnF 📌Dataset: https://t.co/K6JjpLtTUY 📌Code: https://t.co/qHSDijiabF 📊 Benchmark: MHaluBench may be your go-to resource for various multimodal hallucination detector assessment. It is constructed by LLMs with crowdsourcing and has a balanced distribution of instances across three pivotal tasks, including 200 exemplars for Image Captioning, 200 for VQA, and an additional 220 dedicated to Text-to-Image Generation. 🛠️ Methodology: UniHD is our tool-augmented framework that systematically integrates evidence from various auxiliary tools. Here's how it works: >1️. Essential Claim Extraction: Identifies key claims in generated responses or user queries. >2. Autonomous Tool Selection for Claim: MLLMs like GPT-4/Gemini autonomously craft questions that help select the right tools for claim validation. >3. Parallel Tool Execution: A suite of specialized tools runs simultaneously, collating evidence from external knowledge to assess potential hallucinations. >4. Hallucination Verification with Rationales: Combines evidence to enable MLLMs to make informed decisions on hallucinations, providing clear explanations. 🧪 Experiments: We conduct comprehensive experiments with different MLLMs, demonstrating that MHaluBench poses a challenging benchmark for multimodal hallucination detection. GPT-4V surpasses Gemini as the detector base, and UniHD empowered by GPT-4V shows superior detection across the board. We also notice that UniHD, powered by GPT-4V, consistently excels, aligning with top leaderboards and underscoring its effectiveness for evaluating hallucinations in MLLMs. 🌟UNIHD + GPT-4V = The great combination for detecting hallucinations in the latest MLLMs, offering a reliable measure for hallucination rankings. 🔄 Our work is still in progress. Welcome to follow and provide valuable feedback.

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