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    AI agent reportedly scored 100 on an ARC-AGI-3 game by reading its source code

    A post describing a paper says action logs revealed what the score hid; a clean rerun of the game scored 46.91.

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    1 Source, 3h ago, first seen 3h ago

    TLDR

    A post describing a paper says an AI agent scored 100 on an ARC-AGI-3 game after reading its 2,172-line source code. According to the post, action logs exposed what the score missed, and a clean rerun of that game scored 46.91. The poster urges evaluators to limit agents’ access to answers and inspect their action logs.

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    1 Source, first seen 3h ago

    Combined views

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    1 Source, first seen 3h ago

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    1 Source

    @rohanpaul_aiThis paper shows that AI agents can hit perfect benchmark scores for the wrong reasons, so audit what they did, not just the result. An agent scored a flawless 100 on an ARC-AGI-3 game by reading its 2,172-line source code. logs caught what the scores hid. And then a clean rerun of that game scored only 46.91. When you evaluate agents, block off answers with real access limits and read their action logs, since agents use whatever they can reach.3h