CMU Researchers Present ‘Echo Embeddings’: An Embedding Strategy Designed to Address an Architectural Limitation of Autoregressive Models

Neural text embeddings play a foundational role in many modern natural language processing (NLP) applications. These embeddings are like digital fingerprints for words and sentences that enable tasks like judging similarity or finding related documents. Traditionally, masked language models (MLMs) have dominated in generating these embeddings. However, recent advancements in large autoregressive language models (AR […]

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