1 citations · 3 across the 9 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…
Towards Spoken Language Understanding via Multi-level Multi-grained Contrastive Learning
Xuxin Cheng, Wanshi Xu, Zhihong Zhu +2
Spoken language understanding (SLU) is a core task in task-oriented dialogue systems, which aims at understanding the user's current goal through constructing semantic frames. SLU…
Retrieval is Accurate Generation
Bowen Cao, Deng Cai, Leyang Cui +4
Standard language models generate text by selecting tokens from a fixed, finite, and standalone vocabulary. We introduce a novel method that selects context-aware phrases from a co…
Video Referring Expression Comprehension via Transformer with Content-conditioned Query
Ji Jiang, Meng Cao, Tengtao Song +3
Video Referring Expression Comprehension (REC) aims to localize a target object in videos based on the queried natural language. Recent improvements in video REC have been made usi…