VISTA：神经表征的全景视图
VISTA: A Panoramic View of Neural Representations
AI总结：
本文提出 VISTA 可视化流程，将神经网络表征映射到语义二维空间并生成拼贴图，用于揭示内部状态模式；在稀疏自编码器潜变量上的案例研究发现了新属性与解释。
摘要：
我们提出 VISTA（Visualization of Internal States and Their Associations，内部状态及其关联的可视化），这是一种用于可视化探索和解释神经网络表征的新型流程。VISTA 通过将表征映射到语义二维空间，来应对分析现代机器学习模型中庞大的多维空间这一挑战。生成的拼贴图以可视化方式揭示内部表征中的模式和关系。我们通过将 VISTA 应用于稀疏自编码器潜变量来展示其实用性，揭示了新的属性和解释。我们回顾了 VISTA 方法，呈现了案例研究（https://got.drib.net/latents/）中的发现，并讨论了其对机器学习多个领域中神经网络可解释性的意义。
英文摘要：
We present VISTA (Visualization of Internal States and Their Associations), a novel pipeline for visually exploring and interpreting neural network representations. VISTA addresses the challenge of analyzing vast multidimensional spaces in modern machine learning models by mapping representations into a semantic 2D space. The resulting collages visually reveal patterns and relationships within internal representations. We demonstrate VISTA's utility by applying it to sparse autoencoder latents uncovering new properties and interpretations. We review the VISTA methodology, present findings from our case study ( https://got.drib.net/latents/ ), and discuss implications for neural network interpretability across various domains of machine learning.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
