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Found 3 papers, 3 papers with code
Layer-Condensed KV Cache for Efficient Inference of Large Language Models
In this paper, we propose a novel method that only computes and caches the KVs of a small number of layers, thus significantly saving memory consumption and improving inference throughput.
Probabilistic Transformer: A Probabilistic Dependency Model for Contextual Word Representation
Specifically, we design a conditional random field that models discrete latent representations of all words in a sentence as well as dependency arcs between them; and we use mean field variational inference for approximate inference.
Conic10K: A Challenging Math Problem Understanding and Reasoning Dataset
Since the dataset only involves a narrow range of knowledge, it is easy to separately analyse the knowledge a model possesses and the reasoning ability it has.
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