AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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A societal bias evaluation method for large vision-language models (LVLMs) in the era of strong safety guardrails is proposed, finding that all models undesirably use user demographic information in person-irrelevant tasks.
This work proposes COMPACT-VA, a planning-aligned working memory framework built on conditional VQ-VAE, compressing extended context into bounded representations, and evaluates on high-signal dynamic scenarios where historical context is most critical for behavior correctness, and accordingly design behavioral metrics.
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