1 citations · 1 across the 10 of their papers we have counts for
10 papers
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…
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…
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…
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-…
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…
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…
VARGPT: Unified Understanding and Generation in a Visual Autoregressive Multimodal Large Language Model
Xianwei Zhuang, Yuxin Xie, Yufan Deng +4
We present VARGPT, a novel multimodal large language model (MLLM) that unifies visual understanding and generation within a single autoregressive framework. VARGPT employs a next-t…
VASparse: Towards Efficient Visual Hallucination Mitigation via Visual-Aware Token Sparsification
Xianwei Zhuang, Zhihong Zhu, Yuxin Xie +2
Large Vision-Language Models (LVLMs) may produce outputs that are unfaithful to reality, also known as visual hallucinations (VH), which significantly impedes their real-world usag…
SimTxtSeg: Weakly-Supervised Medical Image Segmentation with Simple Text Cues
Yuxin Xie, Tao Zhou, Yi Zhou +1
Weakly-supervised medical image segmentation is a challenging task that aims to reduce the annotation cost while keep the segmentation performance. In this paper, we present a nove…
Joint End-to-End Image Compression and Denoising: Leveraging Contrastive Learning and Multi-Scale Self-ONNs
Yuxin Xie, Li Yu, Farhad Pakdaman +1
Noisy images are a challenge to image compression algorithms due to the inherent difficulty of compressing noise. As noise cannot easily be discerned from image details, such as hi…