Liquid AI Releases Antidoom: Open-Source Fix for Reasoning Model Doom Loops

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Liquid AI has open-sourced Antidoom, a training method called Final Token Preference Optimization (FTPO) designed to eliminate 'doom loops' — a failure mode where reasoning models get stuck in repetitive, non-terminating chains of thought. FTPO works by applying preference optimization specifically on the final token of a reasoning trace, teaching models to recognize and exit unproductive loops rather than continuing them indefinitely. This is a practically significant problem for anyone deploying chain-of-thought or extended-thinking models in production, where doom loops waste compute and degrade user experience. The open-source release means developers can fine-tune their own reasoning models with this technique, or evaluate whether their current models exhibit this behavior. It represents a concrete, reproducible safety and reliability improvement rather than a vague alignment claim.