Establish convergence behavior under changing targets and parameters

Analyze convergence of Temporal-Response Guidance when the response-guided latent targets and model parameters change throughout training.

Background

The theoretical results establish local preservation of the cosine-alignment loss and representation-gradient norm at the point where a target is constructed. During training, however, the student representations, response subspaces, alignment maps, and detached targets are repeatedly recomputed as parameters change.

The paper does not resolve whether this dynamically changing target construction has favorable convergence behavior.

References

The theoretical results concern local loss and representation-gradient norms at target construction; convergence as the targets and model parameters change remains outside this analysis.

— Redirecting Teacher Supervision: Temporal-Response-Guided Latent Distillation for Video-Language Models  (2610.13045 - Lu et al., 9 Oct 2026) in Section 5, Discussion and Limitations