A jointly learned hierarchical index with cross-attention and residual quantization scales exact retrieval in foundational recommendation models, deployed at Meta with additional performance from test-time training on index nodes.
ISBN 9781450384469
2 Pith papers cite this work. Polarity classification is still indexing.
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SPaRSe-TIME introduces a decomposition of time series into saliency-projected low-rank components that delivers competitive accuracy with lower computation and explicit interpretability.
citing papers explorer
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Efficient Retrieval Scaling with Hierarchical Indexing for Large Scale Recommendation
A jointly learned hierarchical index with cross-attention and residual quantization scales exact retrieval in foundational recommendation models, deployed at Meta with additional performance from test-time training on index nodes.
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SPaRSe-TIME: Saliency-Projected Low-Rank Temporal Modeling for Efficient and Interpretable Time Series Prediction
SPaRSe-TIME introduces a decomposition of time series into saliency-projected low-rank components that delivers competitive accuracy with lower computation and explicit interpretability.