AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Recently, Large Language Models (LLMs) have been increasingly able to solve advanced mathematical problems, including many that have been open for decades. This opens the door to expansion of mathematical knowledge at unprecedented scale. Yet, while LLMs may be able to conjecture and prove more and more theorems, it re...
Token-Aware Phase Attention (TAPA) is introduced, a new positional encoding method that incorporates a learnable phase function into the attention mechanism and attains substantially lower perplexity and stronger retrieval performance in the long-context regime than RoPE-style baselines.
Practical LLM agents often operate over multi-turn conversations where success is determined only after the full interaction ends. Most multi-turn RL methods train via on-policy rollouts, but unlike in single-turn RLHF, the policy cannot produce a trajectory alone, since an external environment must respond after each...
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