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GLaS-JEPA is presented, a framework that directly predicts the current encoder's continuous representations at masked positions, without contrastive learning, discrete targets, or separate EMA target encoders, and prevents representation collapse using SIGReg representation-space regularization.
This work presents EMODY Flow, a lightweight flow-matching framework that attaches to a frozen Qwen-3 Omni model and reuses its internal Mimi audio-codecs to condition two parallel DiT generators - one for SMPL-X body pose, one for FLAME facial expressions.
Test-time adaptation (TTA) offers a promising direction for improving speech enhancement models under mismatched acoustic conditions, without requiring access to labeled target data. In this work, we propose a single-utterance TTA method that regularizes a pretrained speech enhancement model using an autoregressive pri...
This work establishes a task-agnostic analysis from three intrinsic per-layer perspectives: compression, geometry, and robustness to perturbations, and introduces the cross-layer Generative Compatibility Matrix (GCM) to evaluate functional transferability.
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