1 citations · 2 across the 3 of their papers we have counts for
9 papers
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…
DiffATR: Diffusion-based Generative Modeling for Audio-Text Retrieval
Yifei Xin, Xuxin Cheng, Zhihong Zhu +2
Existing audio-text retrieval (ATR) methods are essentially discriminative models that aim to maximize the conditional likelihood, represented as p(candidates|query). Nevertheless,…
Audio-text Retrieval with Transformer-based Hierarchical Alignment and Disentangled Cross-modal Representation
Yifei Xin, Zhihong Zhu, Xuxin Cheng +2
Most existing audio-text retrieval (ATR) approaches typically rely on a single-level interaction to associate audio and text, limiting their ability to align different modalities a…