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PuzzleMate: Benchmarking MLLMs for Egocentric Puzzle Assistance

arXiv · AI, language, vision and robotics · article · Sep 13, 2026 · UTC

Personal AI assistants hold the potential to evolve from digital interfaces into embodied companions capable of guiding users through complex physical activities. For these assistants to become integral to daily life, they must do more than identify objects; they must provide precise, step-by-step instructions that align with a user's real-time progress. While Multimodal Large Language Models (MLLMs) show promise in general visual understanding, their ability to deliver grounded, sequential guidance for fine-grained manipulation tasks remains largely unverified. In this paper, we choose the ji

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