Author

Xiao Zhou

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Preprint Sep 2026

AlignDPO: Preference-Gated Alignment for Reducing Hallucination in Decoder-Only TTS

Decoder-only text-to-speech (TTS) models scale efficiently but remain prone to content hallucinations that arise from weak text-speech alignment during autoregressive generation. We find that robustness is governed by a non-monotone relation to the sharpness of the alignment-bearing attention heads: a moderate degree i...

Xiao Zhou, Oisín Turbitt, Kit Bower-Morris et al. · 0 citations

#machine learning Preprint Sep 2026

GrowMTP: Can RL Grow Its Own Draft Head?

Reinforcement learning (RL) post-training drives the frontier capabilities of large language models, with its wall-clock dominated by autoregressive rollout generation. Speculative decoding is an established remedy for this bottleneck, but existing draft heads must be pretrained or warmed up before RL, introducing subs...

Ming-Hua He, Ling-Zhe Zhang, Yuan Liu et al. · 0 citations

Preprint Jul 2026

Hidden Decoding at Scale: Latent Computation Scaling for Large Language Models

Scaling Large Language Models (LLMs) has been driven mainly by enlarging the Transformer backbone, but for an already-strong model this requires another round of costly pretraining. We study whether an existing backbone can keep improving by allocating more computation to each token while leaving the Transformer backbo...

Aiwei Liu, Cheng Shi, Chuhan Wu et al. · 2 citations