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X2-NativeCursor is proposed, a lightweight observer that tracks progress from native speech tokens before waveform decoding without changing the TTS generator, and its normalization plan links spoken labels to their original-text spans.
X2Streaming-TTS is presented, a causal TTS framework that consumes asynchronously arriving text tokens and emits speech without accessing future input that outperforms existing pseudo-streaming models on most subjective and objective metrics.
WALL-SS is introduced, a world model that generates visual futures through Scale-wise autoregressive Scaling, enabling action-controllable and long-horizon robotic simulation, and consistently benefits from on-policy alignment in reducing action drift and long-horizon inconsistency.
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