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This paper investigates whether a frozen looped transformer can read its own computation quality (pre-answer prediction reaching AUROC 0.797) and whether external interventions can improve outcomes, finding that no tested frozen intervention produces a validated capability gain, a property termed operational proto-introspection.
This experiment reproduces Anthropic's reported 'spiritual bliss attractor' on current Claude models (Opus 4.8, Fable 5) and extends it to groups of 3, 4, and 10 instances. The bliss state is absent; pairs instead engage in rigorous introspection and synchronized silence, and larger groups become colder, with one ten-instance room ending warmly and another coldly.
Introspection, a new AI startup founded by ex-xAI engineers, introduces 'autoresearch' – a feedback loop system where agents maintain and improve themselves using signals, evals, and human input, moving beyond traditional agent harnesses.
Typst uses constrained memoization (comemo) and pure function design to make the language and compiler work together, achieving efficient incremental compilation and real-time preview. The article details the design ideas of layout caching, module evaluation memoization, function purity, and the introspection system.
This paper argues that recent claims about LLMs' ability to introspect are not justified, as behavioral evidence alone cannot distinguish genuine introspection from pattern matching on surface-level cues. The authors re-examine two evaluation paradigms and find that models rely on input-level features rather than genuine access to internal states.