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Spectral inheritance allows for a dramatic reduction in training steps while enhancing model accuracy, challenging traditional optimization methods in RLVR.
Forget agents and world models – the future of computing could be learned directly from I/O traces, turning the model itself into the computer.
Forget scaling laws: this work shows you can get SOTA reasoning from sub-billion parameter models with *less* data, if you're smart about curation and resampling.
