… N-gram is a key issue even for lossy approaches. Raj and Whittaker (2003) showed a general
Ngram language model … a succinct way to represent the N-gram language model structure …

… practical situations: the state in a n-gram LM can be succinctly represented with (n − 1) ∗
4 … of n-gram contexts can be processed in parallel. On the downside, the n-gram context …

… Bugram selects high-level tokens that represent the structure and context of the code
using a succinct semantic representation. Take the loop “for (int i=0; i<n; i++) { foo(i); }” as an …

… According to the characteristics of the internet news headlines, short and concise and less
… puts forward N-Gram language model, by constructing two Yuan classification model, to …

… The n-gram language models trained with federated … two languages, American English and
Brazilian Portuguese. This work demonstrates that high-quality n-gram language models can …

… LMs and $n$-gram LMs, a simple and historically relevant class of language models. We …
attention mechanisms can exactly represent any $n$-gram LM, giving us a concrete lower …

… The URL is very concise, and may be composed of … We have introduced an n-gram language
model for this task as a … the n-gram language model and test their impact on the models …

… In this article, we propose the use of suffix arrays to implement n-gram language models with
practically unlimited size n. These unbounded n-grams are called ∞-grams. This approach …

… network based language models can be order of magnitude smaller than compressed n-gram
models, … n-gram models by counting 3 bytes for each n-gram entry. Nonetheless, the 54M …

… We observe that N-gram order affects throughput of the GPU language model much more
than the CPU one. This is likely due to effects of backoff queries, which are more optimized in …