Marktechpost

JUNE 22, 2024

Semantic entropy is a method to detect confabulations in LLMs by measuring their uncertainty over the meaning of generated outputs. This technique leverages predictive entropy and clusters generated sequences by semantic equivalence using bidirectional entailment.

LLM 93

LLM Computational Semantics ChatGPT ML 93

Bugra Akyildiz

APRIL 27, 2024

Whether you are working on a predictive model that computes semantic similarity or the next generative model that is going to beat the LLM benchmarks. Distilabel is the framework for synthetic data and AI feedback for AI engineers that require high-quality outputs, full data ownership, and overall efficiency.

LLM 52

LLM Computational Semantics Generative AI Explainability 52

AWS Machine Learning Blog

JANUARY 24, 2024

Rerank can improve the relevance of search results from lexical or semantic search. Rerank works by computing semantic relevance scores for documents that are retrieved by a search system and ranking the documents based on these scores. Adding Rerank to an application requires only a single line of code change.

Generative AI 139

Generative AI AI AI Large Language Models 139

Heartbeat

JULY 19, 2023

Word embeddings can then be used to predict numerical variables, compute semantic similarity scores across texts, visually represent statistically significant words across multiple dimensions, and much more. Text package: Hugging Face's Transformers in R can be used to convert text variables into word embeddings.

BERT 52

BERT Natural Language Processing NLP Python 52

Marktechpost

SEPTEMBER 15, 2024

Techniques such as BERTSCORE and BARTSCORE employ smaller models to compute semantic similarity and evaluate texts from various perspectives. In addition to that, proxy models can predict LLM performance, reducing computational costs during model selection.

BERT 122

BERT LLM Large Language Models Categorization 122