Ruiyang-061X/Awesome-MLLM-Uncertainty
✨A curated list of papers on the uncertainty in multi-modal large language model (MLLM).
This resource helps AI researchers and practitioners stay current with academic advancements in understanding and quantifying the uncertainty of Multimodal Large Language Models (MLLMs). It provides a curated list of research papers and projects, giving you insights into how MLLMs process and generate information, and how confident their outputs are. Anyone working on improving the reliability, safety, or trustworthiness of AI systems that combine text and images would find this valuable.
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Use this if you need to research the latest techniques and findings related to MLLM uncertainty, calibration, and hallucination detection to build more robust AI.
Not ideal if you are looking for ready-to-use software tools or practical guides for immediate MLLM application development without a research focus.
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Apr 02, 2025
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