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Antidoom is a tool that helps small reasoning models avoid repetitive loops in complex tasks, now reaching Technology Readiness Level. It addresses the issue where models get stuck and repeat words during long thinking traces.
Liquid AI releases Antidoom, an open-source method that fine-tunes reasoning models to break repetitive token loops (doom loops), reducing failure rates from ~23% to 1% on Qwen3.5-4B without retraining or RL.
Liquid AI introduces Antidoom, a method using Final Token Preference Optimization to reduce repetitive doom loops in small reasoning models during inference, cutting loop rates from 10.2% to 1.4% while improving evaluation scores.