用大模型+工具链实现可解释的X光无损检测，提升工业质检可信度。
InsightX Agent: An LMM-based Agentic Framework with Integrated Tools for Reliable X-ray NDT Analysis
- 以大模型为中枢，协调检测与反思工具，实现主动推理。
- 在GDXray+数据集上达到96.54%的检测F1分数。
- 适合需要高可信度和可解释性的工业质检场景。
无损检测（NDT）尤其是X射线检测在工业质量保证中至关重要，但现有基于深度学习的方法往往缺乏交互性、可解释性及自我评估能力，限制了其可靠性与操作员信任。为此，本文提出InsightX Agent，一种基于大得多模态模型（LMM）的智能体框架，旨在实现可靠、可解释且交互式的X射线无损检测分析。不同于传统串行流程，InsightX Agent将大模型作为核心调度者，协同稀疏可变形多尺度检测器（SDMSD）与证据锚定反思（EGR）工具。SDMSD从多尺度特征图生成密集缺陷区域候选，并通过非极大值抑制（NMS）稀疏化，有效检测微小密集目标的同时保持计算效率。EGR工具引导大模型进行类思维链的复核流程，包括上下文评估、单个缺陷分析、误报剔除、置信度重校准与质量保障，以验证并优化SDMSD的初始提案。通过策略性使用与智能调用工具，InsightX Agent突破被动数据处理，实现主动推理，增强诊断可靠性，并整合多源信息提供可解释结论。在GDXray+数据集上的实验表明，InsightX Agent不仅取得96.54%的高检测F1分数，且显著提升分析的可解释性与可信度，凸显基于LMM的智能体框架在工业检测任务中的变革潜力。
原文摘要 · Abstract (English)
Non-destructive testing (NDT), particularly X-ray inspection, is vital for industrial quality assurance, yet existing deep-learning-based approaches often lack interactivity, interpretability, and the capacity for critical self-assessment, limiting their reliability and operator trust. To address these shortcomings, this paper proposes InsightX Agent, a novel LMM-based agentic framework designed to deliver reliable, interpretable, and interactive X-ray NDT analysis. Unlike typical sequential pipelines, InsightX Agent positions a Large Multimodal Model (LMM) as a central orchestrator, coordinating between the Sparse Deformable Multi-Scale Detector (SDMSD) and the Evidence-Grounded Reflection (EGR) tool. The SDMSD generates dense defect region proposals from multi-scale feature maps and sparsifies them through Non-Maximum Suppression (NMS), optimizing detection of small, dense targets in X-ray images while maintaining computational efficiency. The EGR tool guides the LMM agent through a chain-of-thought-inspired review process, incorporating context assessment, individual defect analysis, false positive elimination, confidence recalibration and quality assurance to validate and refine the SDMSD's initial proposals. By strategically employing and intelligently using tools, InsightX Agent moves beyond passive data processing to active reasoning, enhancing diagnostic reliability and providing interpretations that integrate diverse information sources. Experimental evaluations on the GDXray+ dataset demonstrate that InsightX Agent not only achieves a high object detection F1-score of 96.54\% but also offers significantly improved interpretability and trustworthiness in its analyses, highlighting the transformative potential of LMM-based agentic frameworks for industrial inspection tasks.
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