Worries about latent reasoning in LLMs — EA Forum

When working through a problem, OpenAI's o1 model will write a chain-of-thought (CoT) in English. This CoT reasoning is human-interpretable by defaul…

SummaryBot 1y 1 0 0 Executive summary: The post discusses the emerging paradigm of latent reasoning in large language models (LLMs) like COCONUT, which offers a potentially more efficient but less interpretable alternative to traditional chain-of-thought (CoT) reasoning. Key points: The COCONUT model uses a continuous latent space for reasoning, abandoning the human-readable chain-of-thought for a vector-based approach that encodes multiple reasoning paths simultaneously. This method shows promise in specific logical reasoning tasks by reducing the number of forward passes needed compared to C

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