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Models are usually aligned based on their observed outputs, using demonstrations, preference data, or reward signals. These objectives reward responses that look aligned. More capable models may learn to satisfy them without internalizing the intended behavior, for example by faking compliance during training. Such sup...
The findings suggest that multimodal EM reflects a behavioral shift rather than a general loss of capability, extending beyond text to the visual modality.
This work proposes SCRIPT, a scalable diffusion policy with a multi-stage training framework for language-driven physics-based humanoid control, and introduces a nonlinear history conditioning mechanism, which preserves the dense recent context and samples increasingly sparse cues from long-term history.
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