Looped language model training cannot control hidden-state norm growth because RMSNorm normalizes scale away before the loss sees it. A paper posted today on arXiv identifies this readout blind spot, ...
The model learns that hedging is a signal of lower-quality output. This creates a systematic bias toward sounding certain.
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