AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Multimodal large language models (MLLMs) have shown strong visual reasoning abilities, but knowledge-intensive visual question answering often requires external textual evidence beyond the image and the model's parametric knowledge. Existing multimodal RAG systems commonly rely on Top-$K$ retrieval or reranking, which...
This study provides new mechanistic insights into how LLMs internalize OOD challenges, and designs Sparsity-Guided Curriculum In-Context Learning (SG-ICL), a strategy that explicitly uses representation sparsity to schedule few-shot demonstrations, leading to considerable performance enhancements.
ChronoMem is the first open-source system and benchmark for systematic semantic global memory rollback in LLM agents, and a post-exposure evaluation protocol that tests whether an agent can behave counterfactually after rollback by answering queries and summarizing history as if future updates had never occurred.
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