AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Audio-Visual Large Language Models (AV-LLMs) remain prone to cross-modal hallucinations, where one modality incorrectly affects predictions about another. Although contrastive decoding reduces hallucinations in vision-language models, its direct extension to AV-LLMs overlooks a key challenge: different questions requir...
Continual test-time adaptation (CTTA) adapts a source model to an unlabeled test stream whose distribution may change over time. Existing TTA methods often assess prediction reliability using confidence or entropy, which primarily reflect the model's self-certainty for the current sample. In CTTA, accumulated target ob...
This work proposes A-PACK, a two-stage framework that defers audio pruning until query-conditioned multimodal interactions emerge inside the LLM, and shows that audio exhibits higher task-relevant information density and representational diversity per token than video.
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