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zhenyu liu

AwardACL 2026×2ICLR 2026多模态效率与系统可解释性评测与基准对齐与偏好
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2 一作 · 3 篇 · ACL 2026 / ICLR 2026

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2026 顶会论文

3
一作ACL 2026Poster· Natural Language Processing

U ni M o E -Audio: Unified Speech and Music Generation with Dynamic-Capacity Mixture-of-Experts

zhenyu liu · Yunxin Li · Xuanyu Zhang · Qixun Teng · Shenyuan Jiang · Xinyu Chen · Haoyuan Shi · Haolan Chen · Fanbo Meng · Mingjun Zhao · Yu Xu · Yancheng He · Baotian Hu · Haizhou Li · Min Zhang

摘要

Recent advances in unified multimodal models indicate a clear trend towards comprehensive content generation. However, the auditory domain remains a significant challenge, with music and speech often developed in isolation, hindering progress towards universal audio synthesis. This separation ste...

多模态效率与系统评测与基准OpenReview 项目页
一作ACL 2026OralOutstanding Paper· Natural Language Processing

Hierarchical Acoustic-Semantic Modeling: Modality Separation and Semantic Coherence for Full-Duplex SLM s

zhenyu liu · Xuanyu Zhang · Yunxin Li · Qixun Teng · Shenyuan Jiang · Haolan Chen · Mingjun Zhao · Fanbo Meng · Yu Xu · Yancheng He · Baotian Hu · Haizhou Li · Min Zhang

摘要

Developing seamless, high-performance, native intelligent full-duplex Spoken Language Models (SLMs) remains a critical challenge and long-standing goal for the speech and NLP community. Despite notable progress, recent endeavors are fundamentally constrained by severe modality interference, which...

效率与系统对齐与偏好多模态OpenReview 项目页

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