{"blog_title":"fltech - Technology Blog of Fujitsu Research","height":"190","version":"1.0","blog_url":"https://blog-en.fltech.dev/","html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Fblog-en.fltech.dev%2Fentry%2F2026%2F01%2F23%2Fgraphai-lifting-the-veil-of-graph-ai-en\" title=\"Lifting the veil on Graph AI: From black box explainability to self-interpretable models - fltech - Technology Blog of Fujitsu Research\" class=\"embed-card embed-blogcard\" scrolling=\"no\" frameborder=\"0\" style=\"display: block; width: 100%; height: 190px; max-width: 500px; margin: 10px 0px;\"></iframe>","type":"rich","provider_name":"Hatena Blog","author_name":"mahesh_chandran-fltech","url":"https://blog-en.fltech.dev/entry/2026/01/23/graphai-lifting-the-veil-of-graph-ai-en","author_url":"https://blog.hatena.ne.jp/mahesh_chandran-fltech/","image_url":"https://cdn-ak.f.st-hatena.com/images/fotolife/m/maruhashi_koji-fltech/20260122/20260122020938.png","description":"Hello, we are Vempalli Saketh, Siddartha Reddy Thummaluru, Harsh Pandey and Mahesh Chandran from the Artificial Intelligence Research Laboratory at Fujitsu Research of India (FRIPL). We are excited to share our latest research focused on making Graph AI more transparent, trustworthy, and actionable.","categories":["AI"],"title":"Lifting the veil on Graph AI: From black box explainability to self-interpretable models","provider_url":"https://hatena.blog","published":"2026-01-23 10:00:00","width":"100%"}