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xtools-at
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Model Details
Model Provider
xtools-at
Model Tree
xtools-at/Qwen3.5-9B-Claude-3xMerge-UNCENSORED-heretic
Input Modalities
Output Modalities
Supported Functionality
Trace inversion uses the visible reasoning summary as a scaffold. The model aims to preserve the broad order and intent of the supplied bubbles while filling in intermediate steps, producing output in a <think>...</think> block. It is intended for research and synthetic-data workflows rather than as a general-purpose answer model.
The generated trace is not the original hidden reasoning of Claude or any other source model. It is a model-generated reconstruction, and should be labelled as synthetic.
The model uses 11100 training- and 555 evaluation-entries from the following datasets (also used by the NoBubble reference model):
The key fields have been mapped and converted to this dataset: xtools-at/trace-inversion-opus-synthetic
The reasoning bubble is retained in the prompt at inference time.
Include all three ingredients—the problem, the answer, and the reasoning bubble(s)—in the prompt. For example:
text
You are a trace inversion model. Given a problem, a final answer, and several compressed reasoning bubbles, reconstruct a detailed reasoning trace that could plausibly lead to the final answer. Follow these rules:- Treat the reasoning bubbles as the skeleton of the trace.- Expand each bubble into coherent reasoning while preserving the original logical order.- Keep the trace consistent with the problem and the final answer.- Do not introduce unrelated methods, new assumptions, or a different conclusion.- Output only the reconstructed reasoning trace wrapped in <think>...</think>.text
Problem:{problem} Model's final answer:{final_answer} Reasoning Bubbles:{reasoning_bubbles} Reconstruct the full reasoning trace.Expected output shape:
text
<think>{synthetic reconstructed trace}</think>Use the model's supported Qwen3.5 processor/model classes and chat template for inference. Generation settings can affect trace length and style, so validate outputs before adding them to a training dataset.
bibtex
@misc{zhang2026stealreasoning, title = {How to Steal Reasoning Without Reasoning Traces}, author = {Tingwei Zhang and John X. Morris and Vitaly Shmatikov}, year = {2026}, eprint = {2603.07267}, archivePrefix = {arXiv}}You are a trace inversion model. Given a problem, a final answer, and several compressed reasoning bubbles, reconstruct a detailed reasoning trace that could plausibly lead to the final answer.Follow these rules:- Treat the reasoning bubbles as the skeleton of the trace.- Expand each bubble into coherent reasoning while preserving the original logical order.- Keep the trace consistent with the problem and the final answer.- Do not introduce unrelated methods, new assumptions, or a different conclusion.- Output only the reconstructed reasoning trace wrapped in <think>...</think>.Problem:{problem}Model's final answer:{final_answer}Reasoning Bubbles:{reasoning_bubbles}Reconstruct the full reasoning trace.@misc{zhang2026stealreasoning, title = {How to Steal Reasoning Without Reasoning Traces}, author = {Tingwei Zhang and John X. Morris and Vitaly Shmatikov}, year = {2026}, eprint = {2603.07267}, archivePrefix = {arXiv}}