collaborators

9 papers

cs.SD2026

HeartMuLa: A Family of Open Sourced Music Foundation Models

Dongchao Yang, Yuxin Xie, Yuguo Yin +26

We present a family of open-source Music Foundation Models designed to advance large-scale music understanding and generation across diverse tasks and modalities. Our framework con…

eess.AS2026

ASK: Adaptive Self-improving Knowledge Framework for Audio Text Retrieval

Siyuan Fu, Xuchen Guo, Mingjun Liu +7

The dominant paradigm for Audio-Text Retrieval (ATR) relies on dual-encoder architectures optimized via mini-batch contrastive learning. However, restricting optimization to local…

cs.SD2026

SupCLAP: Controlling Optimization Trajectory Drift in Audio-Text Contrastive Learning with Support Vector Regularization

Jiehui Luo, Yuguo Yin, Yuxin Xie +6

Contrastive language-audio pretraining, which aims to unify multimodal representations in a shared embedding space, serves as a cornerstone for building a wide range of application…

cs.SD2025

ATRI: Mitigating Multilingual Audio Text Retrieval Inconsistencies by Reducing Data Distribution Errors

Yuguo Yin, Yuxin Xie, Wenyuan Yang +5

Multilingual audio-text retrieval (ML-ATR) is a challenging task that aims to retrieve audio clips or multilingual texts from databases. However, existing ML-ATR schemes suffer fro…

cs.CL2025

Do we really have to filter out random noise in pre-training data for language models?

Jinghan Ru, Yuxin Xie, Xianwei Zhuang +5

Web-scale pre-training datasets are the cornerstone of LLMs' success. However, text data curated from the Internet inevitably contains random noise caused by decoding errors or unr…

cs.CV2025

VARGPT-v1.1: Improve Visual Autoregressive Large Unified Model via Iterative Instruction Tuning and Reinforcement Learning

Xianwei Zhuang, Yuxin Xie, Yufan Deng +5

In this work, we present VARGPT-v1.1, an advanced unified visual autoregressive model that builds upon our previous framework VARGPT. The model preserves the dual paradigm of next-…