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ICLR 2024 — Best Papers & Talks (ImageGen, Vision, Transformers, State Space Models) ft. Durk Kingma, Christian Szegedy, Ilya Sutskever

Latent Space: The AI Engineer Podcast

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Advancements in Positional Interpolation for Language Models

This chapter explores the innovative concept of positional interpolation (PI) which streamlines extending the context size of language models without extensive retraining. It discusses advanced training techniques, model architectures, and the importance of high-quality data in optimizing performance and computational efficiency. Additionally, it highlights ongoing research initiatives aimed at enhancing large language models and the practical implications of extending context lengths.

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