AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Relational Attention for Data-Efficient Language Modeling
We present Relational BabyLM, a system submission to the BabyLM 2026 challenge that combines two cognitively motivated inductive biases in a single decoder-only Transformer. Architecturally, we replace standard self-attention with a Dual Attention Transformer (DAT), which separates the routing of object-level ("sensory...
Energy-Based Transformers as Predictors of Reading Difficulty
Evidence is found that energy may serve as a single unified predictor where multiple complementary measures have previously been required, suggesting that energy may serve as a single unified predictor where multiple complementary measures have previously been required.