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Training Large Language Models to Reason in Continuous Latent Space

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Manage episode 461129295 series 3448051
Indhold leveret af Arize AI. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Arize AI eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

LLMs have typically been restricted to reason in the "language space," where chain-of-thought (CoT) is used to solve complex reasoning problems. But a new paper argues that language space may not always be the best for reasoning. In this paper read, we cover an exciting new technique from a team at Meta called Chain of Continuous Thought—also known as "Coconut." In the paper, "Training Large Language Models to Reason in a Continuous Latent Space" explores the potential of allowing LLMs to reason in an unrestricted latent space instead of being constrained by natural language tokens.
Read a full breakdown of Coconut on our blog

Learn more about AI observability and evaluation, join the Arize AI Slack community or get the latest on LinkedIn and X.

  continue reading

46 episoder

Artwork
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Manage episode 461129295 series 3448051
Indhold leveret af Arize AI. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Arize AI eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

LLMs have typically been restricted to reason in the "language space," where chain-of-thought (CoT) is used to solve complex reasoning problems. But a new paper argues that language space may not always be the best for reasoning. In this paper read, we cover an exciting new technique from a team at Meta called Chain of Continuous Thought—also known as "Coconut." In the paper, "Training Large Language Models to Reason in a Continuous Latent Space" explores the potential of allowing LLMs to reason in an unrestricted latent space instead of being constrained by natural language tokens.
Read a full breakdown of Coconut on our blog

Learn more about AI observability and evaluation, join the Arize AI Slack community or get the latest on LinkedIn and X.

  continue reading

46 episoder

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