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Qingyang Hong

ACL 2026×2多模态推理对齐与偏好效率与系统强化学习与后训练
新星分资深
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核心/参与5
方向广度10
合作网络3
0 一作 · 2 篇 · ACL 2026

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2026 顶会论文

2
作者位次 #9/9ACL 2026Findings· Findings of ACL

Dual-Reasoner: Bridging Interleaved Atomicity and Streaming Latency via Thinking-while-Talking

Yangzhuo Li · Shengpeng Ji · Yifu Chen · Tianle Liang · Haoyu Yang · Junboli · Jun Fang · Lin Li · Qingyang Hong

摘要

Integrating explicit Chain-of-Thought (CoT) into end-to-end spoken dialogue models enhances intelligence but incurs prohibitive latency. While the “Thinking-while-Talking” paradigm alleviates this delay, it fundamentally compromises block atomicity, severing the logical connection between interle...

推理多模态对齐与偏好OpenReview 项目页
作者位次 #4/5ACL 2026Findings· Findings of ACL

D i TR educio: A Training-Free Acceleration for D i T -Based TTS via Progressive Calibration

Yanru Huo · Ziyue Jiang · Zuoli Tang · Qingyang Hong · Zhou Zhao

摘要

While Diffusion Transformers (DiT) have advanced non-autoregressive (NAR) speech synthesis, their high computational demands remain an obvious limitation. Existing DiT-based text-to-speech (TTS) model acceleration approaches predominantly focus on reducing sampling steps through distillation tech...

效率与系统多模态强化学习与后训练OpenReview 项目页

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