AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This paper introduces InSight, a benchmark for agentic claim verification over interactive visualizations and evaluates state-of-the-art models, revealing that interactive verification remains a non-trivial challenge.
A lightweight, diagnostic saliency map method tailored for text generation over images using transformer models, the current state-of-the-art models in visualization interpretation, is introduced.
The results suggest that language models internally encode whether retrieved evidence is sufficient to support answering, and that this signal can be decoded reliably for RAG triage.
It is suggested that imitating full trajectories helps with playability, while turn-level and teacher-guided training usually improve decision-making and increase the overall score, and small models are performant simply by using careful curation strategies rather than aggressive changes.
A neurosymbolic agent that factors long-horizon household tasks into task-directed visual exploration and constrained symbolic planning and evaluates executable continuations using a domain-independent planning heuristic is presented.
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