Liquid AI open-sources Antidoom to fix doom loops in LLMs

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Liquid AI has open-sourced Antidoom, a method using Final Token Preference Optimization (FTPO) to reduce doom loops in large language models. Built on MetaEra, the technique identifies tokens that trigger loops and trains models to select more coherent alternatives. On LFM2.5-2.6B, loop rates in challenging math and programming tasks decreased from 10.2% to 1.4%; on Qwen3.5-4B, from 22.9% to 1%. The full process takes only hours, and the code and datasets (LiquidAI/antidoom-mix-v1.0) are now publicly available. This AI and crypto development represents a significant step forward in on-chain advancements for model efficiency.
ME AI News: Liquid AI has open-sourced Antidoom, a targeted repair method based on Final Token Preference Optimization (FTPO) to reduce doom loops in reasoning models. The method identifies the first token where a loop begins and trains the model to select coherent alternatives without altering the overall output distribution. On LFM2.5-2.6B, the loop rate dropped from 10.2% to 1.4% in hard math and programming tasks; on Qwen3.5-4B, it fell from 22.9% to 1%. The entire process can be completed in just a few hours, and all code and datasets (LiquidAI/antidoom-mix-v1.0) are now open-sourced. 🔗 Read the original article: https://www.marktechpost.com/2026/07/07/liquid-ai-antidoom-doom-loops-ftpo via AI HOT · https://aihot.virxact.com/items/cmraw21y401jhihog3tcrfsp4 (Source: AiHot)
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