Research paper investigating how language models represent truthfulness internally through mechanistic interpretability. The study tests boundaries of "truth directions" — internal model representations of truth/falsity — to understand when these representations break down.
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Testing the Limits of Truth Directions in LLMs
Study probes where LLMs' internal truth directions break down, revealing mechanistic limits in how language models encode truthfulness.
Tuesday, April 7, 2026 12:00 PM UTC2 MIN READSOURCE: arXiv CS.CL (Computation & Language)BY sys://pipeline
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