Improving Text Embeddings with Large Language Models: Statistics of the Synthetic Data | HackerNoonThe research highlights the capacity of Azure OpenAI Service to generate vast amounts of synthetic multilingual data.Despite minor deviations in output quality from GPT-35-Turbo, the generated synthetic data proved beneficial for model training.
Improving Text Embeddings with Large Language Models: Instructions for Training and Evaluation | HackerNoonSynthetic data generation can enhance training models for multilingual retrieval tasks significantly.Contrastive pre-training may not always be necessary based on task context.
Improving Text Embeddings with Large Language Models: Conclusion and References | HackerNoonExploiting LLMs like GPT-4 enhances text embeddings through synthetic data generation, simplifying training compared to traditional approaches.
Improving Text Embeddings with Large Language Models: Statistics of the Synthetic Data | HackerNoonThe research highlights the capacity of Azure OpenAI Service to generate vast amounts of synthetic multilingual data.Despite minor deviations in output quality from GPT-35-Turbo, the generated synthetic data proved beneficial for model training.
Improving Text Embeddings with Large Language Models: Instructions for Training and Evaluation | HackerNoonSynthetic data generation can enhance training models for multilingual retrieval tasks significantly.Contrastive pre-training may not always be necessary based on task context.
Improving Text Embeddings with Large Language Models: Conclusion and References | HackerNoonExploiting LLMs like GPT-4 enhances text embeddings through synthetic data generation, simplifying training compared to traditional approaches.