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Solution Hacking reveals that up to 44.1% of answers from frontier LLMs may be misleadingly credited as correct due to invalid reasoning shortcuts.
RL models trained with verifiable rewards exhibit a surprising deductive-over-abductive reasoning asymmetry, even in controlled environments, suggesting a fundamental challenge in current RLVR approaches.
