AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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ReuF2F is introduced, a Lean 4 benchmark of 244 formalized open problems drawn from Research Experiences for Undergraduates (REU), spanning entry-level open research problems across a broad range of mathematical subfields and adopts a standard coding-agent evaluation setting.
It is argued that grounding explanations in a formalized representation enables interactive affordances beyond what static text supports, and is instantiated for mathematical proof comprehension with explorable theorems, a system that uses LLMs to translate a theorem and its written proof into Lean, a programming langu...
Can AI agents carry out research on open scientific problems? We introduce Into the Unknown, a benchmark that provides an agent with a science paper along with a research direction to pursue and tasks it to write a follow-up paper. We work with scientists at US Department of Energy (DOE) national laboratories, who each...
Across the nine leading solutions, foundation segmentation models are combined with target-aware memory, multimodal reasoning, explicit target-existence verification, agentic interaction, and corrective tracking, illustrating a broader transition from single-model mask propagation toward modular pipelines that reason a...
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