Unverified50% confidenceCautionExact time
Only weights that natively support MTP training can activate this feature on the inference side.
1
Sources
50%
Confidence
Long-term
Relevance
10/1/2026
First Seen
Sources
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Related Claims
UnverifiedRetaining MTP capability during fine-tuning is a technical challenge, because if the training pipeline does not correctly handle the extra prediction head parameters, the weights of the MTP module will be corrupted or reset.78% similarUnverifiedRestricting training data or fine-tuning directions can only affect a model's default behavior, and cannot prevent technically capable individuals from bypassing restrictions through prompt engineering or model modification.68% similarUnverifiedThe study concludes that its findings constrain token-level explanations but do not truly identify the underlying mechanism of feature transfer during training.66% similarUnverifiedCurrent mainstream benchmarks and training frameworks only schedule events belonging to the benchmark itself, and cannot natively handle the various events generated during agent operation.63% similar
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