Our method steers LLMs away from toxic words in real time, guiding generation toward safe alternatives using the output layer’s SVD decomposition. No retraining is needed, while fluency and context are preserved.

This paper proposes a constrained posterior sampling approach for time series generation with hard constraints.

We investigate how human-interpretable concepts evolve in diffusion models through the generative process.