mlsanityData to 7 Oct 2026

Power-LLaVA: Large Language and Vision Assistant for Power Transmission Line Inspection

arXiv 2407.19178 ↗First posted 27 Jul 2024cs.CV eess.SPcited by 3

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Abstract (arXiv)

The inspection of power transmission line has achieved notable achievements in the past few years, primarily due to the integration of deep learning technology. However, current inspection approaches continue to encounter difficulties in generalization and intelligence, which restricts their further applicability. In this paper, we introduce Power-LLaVA, the first large language and vision assistant designed to offer professional and reliable inspection services for power transmission line by engaging in dialogues with humans. Moreover, we also construct a large-scale and high-quality dataset specialized for the inspection task. By employing a two-stage training strategy on the constructed dataset, Power-LLaVA demonstrates exceptional performance at a comparatively low training cost. Extensive experiments further prove the great capabilities of Power-LLaVA within the realm of power transmission line inspection. Code shall be released.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 24 of its 33 references that are in the map. First posted on arXiv 27 Jul 2024.

Builds on

24 of 33 references.

References · 24

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12 more
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Cited by year

Citing papers per year: 2024: 2; 2025: 1.

3 papers.

  1. 2024HumanVLM: Foundation for Human-Scene Vision-Language Modelcited by 8
  2. 2024EF-LLM: Energy Forecasting LLM with AI-assisted Automation, Enhanced Sparse Prediction, Hallucination Detectioncited by 6
  3. 2025InspectVLM: Unified in Theory, Unreliable in Practicecited by 0