Liquid AI this week open-sourced Antidoom, specifically fixing the doom loop of reasoning models — when a model gets stuck in a "Wait…Alternatively…But…" cliché loop until the context is exhausted, the essence is that high-prior tokens like "Wait", "So", "the", "But", "Alternatively" are repeatedly selected under uncertainty, and the preceding loop further raises the probability of the same sequence, while the low-temperature sampling commonly used by reasoning models (e.g., temperature=0) almost cuts off the possibility of escape. The common inference-time fix is to add a repetition_penalty, but the Liquid team thinks this is a band-aid that will incidentally harm other capabilities. Antidoom's core is FTPO (Final Token Preference Optimization): first generate a batch of "will loop" samples at low temperature, locate the "loop start" token, use the model's own top-k candidates as the chosen token, train a LoRA with rank=128256, lr=4e-62e-5 for one epoch. The objective function only does preference optimization at that one position, with the reference distribution constrained by logit-space KL rather than softmax, avoiding collateral damage to unrelated tokens; the early-stop threshold chosen_win=0.35 is key, overshooting will trigger new loops. The effect is immediate: LFM2.5-2.6B's early checkpoint doom-loop rate drops from 10.2% to 1.4%, Qwen3.5-4B from 22.9% to 1.0%, and eval scores rise across multiple reasoning benchmarks — the training set itself didn't teach the model any new knowledge, it purely released "what it could already do, but was just stuck by itself". Code, data, and the FTPO implementation are all open-sourced at github.com/Liquid4All/antidoom, and a round can be run on 1-2 MI325s in 2-3 hours. For teams doing RL post-training or deploying reasoning models, Antidoom is a very practical "loop-repair" pipeline: running it once before large-scale RL, common failure modes can be compressed to the 1% magnitude. The "single-token preference optimization + logit-space KL" thinking of FTPO will likely spread to local failure mode repair like hallucination and format drift.