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Wenxi Chen

ACL 2026×3多模态效率与系统对齐与偏好可解释性数据与预训练
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一作贡献30
核心/参与10
方向广度10
合作网络3
1 一作 · 3 篇 · ACL 2026

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2026 顶会论文

3
一作ACL 2026Poster· Natural Language Processing

SAC : Neural Speech Codec with Semantic-Acoustic Dual-Stream Quantization

Wenxi Chen · Ruiqi Yan · Yushen Chen · Zhikang Niu · Ziyang Ma · Xiquan Li · Yuzhe Liang · Wenhanlin · Shunshun Yin · Ming Tao · Xinsheng Wang · Xie Chen

摘要

Speech codecs that convert continuous speech signals into discrete tokens have become essential for speech language models. However, existing codecs struggle to balance high-quality reconstruction with semantically rich representations, limiting their effectiveness in both generative and understa...

可解释性多模态效率与系统OpenReview 项目页
作者位次 #4/7ACL 2026Poster· Natural Language Processing

F ine LAP : Taming Heterogeneous Supervision for Fine-grained Language-Audio Pretraining

Xiquan Li · Xuenan Xu · Ziyang Ma · Wenxi Chen · Haolin He · Qiuqiang Kong · Xie Chen

摘要

Contrastively pretrained audio–language models (e.g., CLAP) excel at clip-level understanding but struggle with frame-level tasks.Existing extensions fail to exploit the varying granularity of real-world audio–text data, where massive clip-level textual descriptions coexist with limited frame-lev...

多模态数据与预训练对齐与偏好OpenReview 项目页
作者位次 #5/6ACL 2026Poster· Natural Language Processing

M ean A udio: Fast and Faithful Text-to-Audio Generation with Mean Flows

Xiquan Li · Junxi Liu · Yuzhe Liang · Zhikang Niu · Wenxi Chen · Xie Chen

摘要

Recent years have witnessed remarkable progress in Text-to-Audio Generation (TTA), providing sound creators with powerful tools to transform inspirations into vivid audio. Yet despite these advances, current TTA systems often suffer from slow inference speed, which greatly hinders the efficiency...

效率与系统对齐与偏好多模态OpenReview 项目页

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