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cs.CL2025
Lessons from Studying Two-Hop Latent Reasoning
Mikita Balesni, Tomek Korbak, Owain Evans
Large language models can use chain-of-thought (CoT) to externalize reasoning, potentially enabling oversight of capable LLM agents. Prior work has shown that models struggle at tw…
cs.CL2024
Looking Inward: Language Models Can Learn About Themselves by Introspection
Felix J Binder, James Chua, Tomek Korbak +6
Humans acquire knowledge by observing the external world, but also by introspection. Introspection gives a person privileged access to their current state of mind (e.g., thoughts a…
cs.CL2024
The Reversal Curse: LLMs trained on "A is B" fail to learn "B is A"
Lukas Berglund, Meg Tong, Max Kaufmann +4
We expose a surprising failure of generalization in auto-regressive large language models (LLMs). If a model is trained on a sentence of the form "A is B", it will not automaticall…