Liquid AI Proposes Antidoom Training to Eliminate Model Inference Loops
max_paperclips · x · 2026-08-02
Reasoning models often fall into repetitive 'doom loops' during complex tasks. Liquid AI introduced 'Antidoom', a new method using Final Token Preference Optimization (FTPO) to address this.
The technique identifies the exact token starting a loop and trains the model to prefer coherent alternatives at that position, leaving the rest of the distribution untouched. On the LFM2.5-2.6B model, this reduced loop occurrence in math and coding tasks from 10.2% to 1.4%, with overall evaluation scores improving as a result.
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