ScaffoldAgent introduces a utility-guided framework for dynamic outline optimization in open-ended deep research. It models outline evolution through Expansion, Contraction, and Revision operations, guided by a feedback mechanism that evaluates retrieval gain, structural coherence, and generation quality. Experiments show it improves long-form report generation and factual grounding compared to existing agents.
ScaffoldAgent: Utility-Guided Dynamic Outline Optimization
OpenAI releases GPT-6 Astra with strong 3D rendering and computer use
OpenAI has released GPT-6 Astra, a new model that significantly outperforms its predecessor GPT-5.6 across writing, math, and coding benchmarks. The release highlights the model's exceptional capabilities in 3D rendering, animation, and graphical user interface interaction.
OpenAI claims AI-assisted Navier-Stokes singularity result using 10,000 agents
OpenAI-affiliated accounts reported that an AI-assisted effort produced a result related to the Navier-Stokes existence and regularity problem, one of the Millennium Prize Problems. The claim states that approximately 10,000 agents collaborated on the task after being trained for roughly a year using multi-agent reinforcement learning.
OpenAI internal system proves Navier–Stokes equations can develop finite-time singularities
OpenAI reports that an internal AI system has produced a proof showing that the dynamics of the Navier-Stokes equations for fluid motion can develop a singularity in finite time. The solution, derived by a multi-agent system powered by a model significantly more capable than GPT-6 Astra, establishes statement "C" of the Millennium Prize formulation.
DisCo distills GitHub repos into 5,000+ AI research skills
Researchers present DisCo, a skill-powered autonomous agent designed to bridge the gap in operational knowledge for machine learning research by distilling expertise from code repositories. The system condenses widely used open-source projects into reusable, verified skills through two complementary forms: task-agnostic distillation of general ecosystems and task-oriented generation for specific needs.
DisCo distills GitHub repositories into AI4AI skills to boost research agent performance
The authors present DisCo, a skill-powered research agent designed to bridge the gap in operational knowledge by distilling domain-specific know-how from external sources. The system condenses widely used machine learning repositories into reusable, verified skills through two complementary forms: task-agnostic distillation for broad utility and task-oriented distillation for specific needs.