Tonio Wandmacher and Jean-Yves Antoine. 2007. Methods to Integrate a Language Model with Semantic Information for a Word Prediction Component. In Proceedings of ...

Jan 30, 2008 · We present and evaluate here several methods that integrate LSA-based information with a standard language model: a semantic cache, partial ...

We present and evaluate here several methods that integrate LSA-based information with a standard language model: a semantic cache, partial reranking, and ...

Most current word prediction systems make use of n-gram language models (LM) to es- timate the probability of the following word in a phrase.

This work explores the predictive powers of Latent Semantic Analysis (LSA), a method that has been shown to provide reliable information on long-distance ...

Bibliographic details on Methods to Integrate a Language Model with Semantic Information for a Word Prediction Component.

Mar 13, 2024 · It captures semantic and contextual information by mapping every word in the lexicon to a dense vector representation. The model can be trained ...

It assists in mapping semantically similar words to geometrically close embedding vectors. It uses the cosine similarity metric to measure semantic similarity.

Jan 19, 2022 · Next-token prediction is basically: we have [as a] given all the previous words in context, [and] we just want to predict the next word.

May 23, 2024 · This study models language comprehension by using the next sentence prediction (NSP) task to investigate mechanisms of discourse-level comprehension.