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Liquid AI Open-Sources Antidoom: A Final Token Preference Optimization (FTPO) Method that Reduces Doom Loops in Reasoning Models

Liquid AI released Antidoom, an open-source method targeting doom loops in reasoning models. Using FTPO, it retrains only the token that starts a loop, reducing loop rates from 10.2% to 1.4% on LFM2.5-2.6B and from 22.9% to 1% on Qwen3.5-4B.

SourceMarkTechPostAuthor: Asif Razzaq
Liquid AI Open-Sources Antidoom: A Final Token Preference Optimization (FTPO) Method that Reduces Doom Loops in Reasoning Models
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Key points

  • Antidoom reduces doom loops by retraining only the first loop-start token.
  • FTPO spreads probability across multiple coherent alternatives.
  • LFM2.5-2.6B looping fell from 10.2% to 1.4%; Qwen3.5-4B from 22.9% to 1%.
  • Full stack is open source; pipeline runs in a few hours.

Highlights and analysis are generated automatically and may contain errors. Check the original source.