At this year’s International Conference on Machine Learning (ICML), Amazon researchers have more papers on bandit problems and differential privacy, two topics of perennial interest. But they also explore a number of other topics with a mixture of theoretical analysis and practical application. Neurral calculation adjustment Neurral calculation adjustment Means tailoring the number of calculations … Read more
Automatic Speech Recognition (ASR) models that convert speech into text come in two varieties, causal and non -alausal. A causal model treats speech when it comes in; To determine the correct interpretation of the current frame (discreet chunk) of sound, it can only use the frames that preceded it. A non -causal model waits until … Read more
In the rapidly evolving domain of large language models (LLMs), the accord evaluation of models of retrieval-augmented generation (RAG) is important. In this blog, we introduce a groundbreaking methodology that uses an automated exam process, improved after the product responsible theory (IRT), to evaluate the practical accuracy of RAG models on specific tasks. Our approval … Read more
Amazon’s papers on International Conference on Machine Learning (ICML) Lean – as the conference as a whole – against the theoretical. Although some papers deal with important applications for Amazon, such as anomaly detection and automatic speech recognition, they are most concerned with more-general items related to machine learning, such as responsible AI and transfer … Read more
The documents used to train a large language model (LLM) are typically linked to forming a single “super document”, which is then divided into sequences, as the model’s context length. This improves exercise efficiency, but often results in unnecessary trunkings where individual documents are divided across successive sequences. Related content Coherent parameter handling and prior … Read more