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Found 5 papers, 4 papers with code
Quantized Embedding Vectors for Controllable Diffusion Language Models
To further enhance their portability of independent deployment as well as improve their stability evaluated by language perplexity, we propose a novel approach called the Quantized Embedding Controllable Diffusion Language Model (QE-CDLM).
Fast and exact fixed-radius neighbor search based on sorting
Fixed-radius near neighbor search is a fundamental data operation that retrieves all data points within a user-specified distance to a query point.
Fast and explainable clustering based on sorting
We introduce a fast and explainable clustering method called CLASSIX.
An efficient aggregation method for the symbolic representation of temporal data
This variant utilizes a new aggregation approach tailored to the piecewise representation of time series.
A comparison of LSTM and GRU networks for learning symbolic sequences
We explore the architecture of recurrent neural networks (RNNs) by studying the complexity of string sequences it is able to memorize.
