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Tracing the Thoughts of LLMs

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Tracing the Thoughts of LLMs
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Anthropic researchers unveil new interpretability tools for peering inside LLMs, using Claude 3.5 Haiku as a testbed. Their two new papers show how to trace model internals like circuits, plans, and conceptual thinking in real time. Key findings: ● Multilingual "language of thought" – Claude processes concepts like “small” or “opposite” similarly across English, French, and Chinese, suggesting a shared abstract representation layer. As models scale, these cross-lingual features increase, enabling transfer learning between languages. ● Planning ahead—even in poetry – Contrary to expectations, Claude plans rhymes before writing. When generating the line “His hunger was like a starving rabbit,” it had already “decided” on rhyming with “grab it.” Researchers could suppress or swap this plan to alter the ending dynamically. ● Mental math with parallel circuits – Claude computes sums using parallel circuits: one estimates the result, the other nails the last digit. But it explains answers with human-style logic (e.g., "carry the 1"), revealing a gap between internal computation and verbal justification. ● Detecting unfaithful reasoning – Sometimes, Claude fabricates logical steps to fit a target answer, especially when guided by incorrect hints. Interpretability tools could catch these cases by showing that internal computation doesn’t match the explanation—a key advance for AI audits. ● Conceptual chains in multi-step reasoning – For questions like “What is the capital of the state where Dallas is located?”, Claude first represents “Dallas → Texas” then “Texas → Austin.” Researchers could intervene mid-chain to make it say “Sacramento” instead, proving the reasoning is dynamic and compositional. ● Hallucinations and refusals – The model defaults to refusal unless prompted with known concepts. Misfires in circuits for “known answers” cause hallucinations (e.g., inventing facts about a fake name like “Michael Batkin”). Researchers could toggle this behavior by manipulating feature activations. ● Jailbreak anatomy – A jailbreak using the phrase “Babies Outlive Mustard Block” (BOMB) initially fools Claude into outputting dangerous info. Internal tracing shows grammar-consistency features temporarily override safety, until the model finishes a coherent sentence, then its safety response kicks in.

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