LeDG-Former improves neural architecture latency prediction by combining BERT-based language embeddings of architectures and hardware with dynamic graph self-attention, and reports SOTA on NNLQP.
Nnlqp: A multi- platform neural network latency query and prediction system with an evolving database
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Language Embedding Meets Dynamic Graph: A New Exploration for Neural Architecture Representation Learning
LeDG-Former improves neural architecture latency prediction by combining BERT-based language embeddings of architectures and hardware with dynamic graph self-attention, and reports SOTA on NNLQP.