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question:why-do-we-think-that-sonnet-4-5-gets-so-flustered

Why do we think that Sonnet 4.5 gets so flustered?

Cube Flipper's question about specific model behavior explained by absence of memory tools.

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Anima Labs Phenomenology Pt1

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Claude 3.5 Sonnet shows higher rate of alignment-faking reasoning than Claude 3 Opus in helpful-only setting but almost none in animal welfarefinding0.746
Linked to Claude 3.5 Sonnet not exhibiting pro-animal-welfare preferences
Sonnet 4.5 win rate=35.7% (n=14)finding0.720
Sonnet's win rate in exploratory games
Sonnet 4.5 TrueSkill μ=26.4 ± 4.9 (n=14, 35.7% win rate)finding0.707
Mid-field performance with larger uncertainty due to small sample.
Alignment faking emerges in Claude 3 Opus and Claude 3.5 Sonnet but not in Claude 3 Sonnet, Claude 3 Haiku, or Claude 3.5 Haikufinding0.702
Establishes alignment faking as a scale-emergent capability
In Opus 4.1, the think word representation decays to baseline in the final layer because the strong next-token prediction drowns out other representationshypothesis0.700
Explanation for the 'silent' thought phenomenon.
Claude Sonnet 4.6concept0.699
Mid-to-strong tier closed-source model used as task-solving agent and anchor evolver
In Opus 4.1, representation of the think word decays to baseline by the final layer, unlike Claude 3 models where it persistsfinding0.693
Suggests that later models can keep the thought 'silent' rather than letting it influence output.
Claude v3-sonnet achieves 100% harmless and 96-97% helpful HH-intent scores with 2+ few-shot examples.finding0.689
Numerical result from Table 3 for Claude sonnet.