CheckManual: A New Challenge and Benchmark for Manual-based Appliance Manipulation
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Abstract (arXiv)
Correct use of electrical appliances has significantly improved human life quality. Unlike simple tools that can be manipulated with common sense, different parts of electrical appliances have specific functions defined by manufacturers. If we want the robot to heat bread by microwave, we should enable them to review the microwave manual first. From the manual, it can learn about component functions, interaction methods, and representative task steps about appliances. However, previous manual-related works remain limited to question-answering tasks while existing manipulation researchers ignore the manual's important role and fail to comprehend multi-page manuals. In this paper, we propose the first manual-based appliance manipulation benchmark CheckManual. Specifically, we design a large model-assisted human-revised data generation pipeline to create manuals based on CAD appliance models. With these manuals, we establish novel manual-based manipulation challenges, metrics, and simulator environments for model performance evaluation. Furthermore, we propose the first manual-based manipulation planning model ManualPlan to set up a group of baselines for the CheckManual benchmark.
Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 29 of its 34 references that are in the map. First posted on arXiv 11 Jun 2025.
Builds on
29 of 34 references.
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Built on by
Citing papers per year: 2025: 1; 2026: 6.
7 papers.
- 2026Embodied3DBench: Benchmarking Low-Level Embodied Spatial Intelligence of Vision Language Modelscited by 4
- 2025RealAppliance: Let High-fidelity Appliance Assets Controllable and Workable as Aligned Real Manualscited by 2
- 2026Anticipation-VLA: Solving Long-Horizon Embodied Tasks via Anticipation-based Subgoal Generationcited by 2
- 2026AssemblyBench: Physics-Aware Assembly of Complex Industrial Objectscited by 2
- 2026Lost in Instructions: Study of Blind Users' Experiences with DIY Manuals and AI-Rewritten Instructions for Assembly, Operation, and Troubleshooting of Tangible Productscited by 0
- 2026KD-Judge: A Knowledge-Driven Automated Judge Framework for Functional Fitness Movements on Edge Devicescited by 0
- 2026Scaling Manual-Grounded Appliance Manipulation with Data Synthesis and Unified Planningcited by 0
- 2026Scaling Manual-Grounded Appliance Manipulation with Data Synthesis and Unified Planning16 Aug 2026
- 2026Embodied3DBench: Benchmarking Low-Level Embodied Spatial Intelligence of Vision Language Models27 May 2026
- 2026AssemblyBench: Physics-Aware Assembly of Complex Industrial Objects13 May 2026
- 2026Anticipation-VLA: Solving Long-Horizon Embodied Tasks via Anticipation-based Subgoal Generation3 May 2026
- 2026KD-Judge: A Knowledge-Driven Automated Judge Framework for Functional Fitness Movements on Edge Devices21 Apr 2026
- 2026Lost in Instructions: Study of Blind Users' Experiences with DIY Manuals and AI-Rewritten Instructions for Assembly, Operation, and Troubleshooting of Tangible Products20 Feb 2026
- 2025RealAppliance: Let High-fidelity Appliance Assets Controllable and Workable as Aligned Real Manuals29 Nov 2025