AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Graph few-shot class-incremental learning (GFSCIL) requires a model to continually recognize emerging classes from only a few labeled nodes while preserving previously acquired knowledge. Beyond the catastrophic forgetting inherited from conventional graph continual learning, GFSCIL presents two distinctive challenges:...
Large language models (LLMs) have achieved remarkable success across diverse applications, yet their generic training paradigm limits effectiveness in user-specific scenarios. LLM personalization aims to adapt large models to individual users or user groups by incorporating preferences, histories, and contextual signal...
PAC-Bayes-regularized Meta-LoRA is proposed, which uses a meta-learned LoRA initialization as both the adaptation start and prior center, while adjusting update strength according to support-set size and predictive uncertainty to limit overfitting under sparse or ambiguous evidence.
It is argued that numerical format design is itself a first-class lever for stable FP4 training, and the first systematic study of FP4 LLM pretraining on energy-efficient Huawei Ascend NPUs is presented.
Ide Search is proposed, a framework that systematically integrates a dynamic"Idea Bank" into Tree Search, a framework that systematically integrates a dynamic bank of ideas into Tree Search, and reliably breaks the plateau of a strong pure Tree Search baseline.
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