Edge 367: Understanding Multi-Chain Reasoning in LLMs
Was this email forwarded to you? Sign up here Edge 367: Understanding Multi-Chain Reasoning in LLMsOne of the most interesting techniques used for more complex reasoning in LLMs.
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💡 ML Concept of the Day: Understanding Multi-Chain ReasoningChain of Thought(CoT) methods are currently considered the most prominent techniques in LLM reasoning. Despite its performance effectiveness, CoT methods have known limitations in terms of evaluating concurrent chains of reasoning. Traditionally, these models would sample several reasoning chains and use a voting system to decide on the final answer, often overlooking the individual steps taken within each chain. However, this process, while enhancing performance, failed to account for the intricate connections between the steps in different chains, nor did it provide a comprehensive explanation for its conclusions... Subscribe to TheSequence to read the rest.Become a paying subscriber of TheSequence to get access to this post and other subscriber-only content. A subscription gets you:
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