AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Experiments on a carefully curated icon dataset reveal structured metonymic circuits, in which perceptual primitives dominate early layers and object-like anchors precede abstract targets, which validate that metonymic intermediates are functionally involved in grounding abstract concepts.
Recent Test-Time Training (TTT) architectures compress context into fast weights that are updated online and queried as memory. Existing TTT designs keep this memory private to each layer: it recurs only over time, and depth merely indexes L separate memories. We argue that memory ownership need not be tied to depth, a...
This work introduces SVGLM, a framework that uses scalable vector graphics (SVG) primitives to connect text and image in reasoning tasks, and exploits the duality of SVG as both image description and text instructions, yielding a more compact, interpretable solution to equip general VLMs with the capability of generati...
The Very Big Video Reasoning (VBVR) Dataset is introduced, an unprecedentedly large-scale resource spanning 200 curated reasoning tasks following a principled taxonomy and over one million video clips, approximately three orders of magnitude larger than existing datasets.
By integrating an environment-based verifier framework, this paper enhances LLM agents'ability to comprehend task rules and complete tasks, promoting both safer and more interpretable collaboration in AI systems.
SimLife is introduced, a scalable platform for simulating long-term household life with rich visual observations, ground-truth action logs, and synthetic dialogues with audio that evaluates long-context pattern understanding: the ability to infer latent behavioral rules from weeks or months of everyday observations.
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