AI Briefing#explainable-ai
The latest AI and developer news about #explainable-ai, with the original source and a short summary.
The latest AI and developer news about #explainable-ai, with the original source and a short summary.
The open-source library implements the Graph of Agentic Thoughts framework to capture decision reasoning and rejected alternatives in LangGraph applications.
Thore Graepel, a core member of the AlphaGo team, left Google DeepMind to pursue research into systems that maintain explicit, auditable epistemic states rather than relying on next-token prediction.
The study reveals how TokenGT models reconstruct graph incidence through node-ID matching to solve tasks like degree calculation and shortest-path distance.
LG AI Research has developed SISE, a new image recognition explanation technology that overcomes the limitations of existing XAI models.
Microsoft Research unveiled the GCT framework, which uses LLMs to explain and verify how the brain processes language.
At ICAIF 2025, reinforcement learning, investment strategy, and reliability research were confirmed as the core currents of financial AI.
At the 6th Kakao Tech Meet, Kakao revealed a use case for leveraging LLMs to generate natural language sentences from spam classification results, providing operators with the rationale behind decisions.
This defines the concept of Explainable AI (XAI) and introduces use cases for improving the performance and user experience of Computer Vision and NLP models.