12 papers
Revitalizing Medical Time Series with Vision-Informed Retrieval: A Vision-Language Perspective
Guoqi Yu, Juncheng Wang, Shujun Wang
Medical time series (MedTS) underpin many clinical classification tasks, yet existing methods usually represent them only as numerical sequences and underuse the morphology that is…
Beyond Time Shifts: Adapting Omni-LLM as a Reference-Free Evaluator for Generative Audio-Visual Models
Yijie Qian, Juncheng Wang, Chao Xu +6
As audio-visual generative models evolve into world simulators, cross-modal synchronization stands as a critical proxy for assessing the consistency of world dynamics and causality…
DenseControl: Instance-Level Controllable Synthesis of Dense Crowd Image
Juncheng Wang, Lei Shang, Wang Lu +2
In this paper, we introduce DenseControl, a novel pipeline for generating dense crowd images. Specifically, DenseControl meticulously positions and sizes each generated instance to…
Decentralized Attention Fails Centralized Signals: Rethinking Transformers for Medical Time Series
Guoqi Yu, Juncheng Wang, Chen Yang +3
Accurate analysis of medical time series (MedTS) data, such as electroencephalography (EEG) and electrocardiography (ECG), plays a pivotal role in healthcare applications, includin…
Guided by the Plan: Enhancing Faithful Autoregressive Text-to-Audio Generation with Guided Decoding
Juncheng Wang, Zhe Hu, Chao Xu +5
Autoregressive (AR) models excel at generating temporally coherent audio by producing tokens sequentially, yet they often falter in faithfully following complex textual prompts, es…
Think Before You Move: Latent Motion Reasoning for Text-to-Motion Generation
Yijie Qian, Juncheng Wang, Yuxiang Feng +7
Current state-of-the-art paradigms predominantly treat Text-to-Motion (T2M) generation as a direct translation problem, mapping symbolic language directly to continuous poses. Whil…
An Anatomy of Vision-Language-Action Models: From Modules to Milestones and Challenges
Chao Xu, Suyu Zhang, Yang Liu +11
Vision-Language-Action (VLA) models are driving a revolution in robotics, enabling machines to understand instructions and interact with the physical world. This field is exploding…
Exploring Scale Shift in Crowd Localization under the Context of Domain Generalization
Juncheng Wang, Lei Shang, Ziqi Liu +5
Crowd localization plays a crucial role in visual scene understanding towards predicting each pedestrian location in a crowd, thus being applicable to various downstream tasks. How…
Language Model Based Text-to-Audio Generation: Anti-Causally Aligned Collaborative Residual Transformers
Juncheng Wang, Chao Xu, Cheng Yu +5
While language models (LMs) paired with residual vector quantization (RVQ) tokenizers have shown promise in text-to-audio (T2A) generation, they still lag behind diffusion-based mo…
Synchronized Video-to-Audio Generation via Mel Quantization-Continuum Decomposition
Juncheng Wang, Chao Xu, Cheng Yu +4
Video-to-audio generation is essential for synthesizing realistic audio tracks that synchronize effectively with silent videos. Following the perspective of extracting essential si…
ReFocus: Reinforcing Mid-Frequency and Key-Frequency Modeling for Multivariate Time Series Forecasting
Guoqi Yu, Yaoming Li, Juncheng Wang +4
Recent advancements have progressively incorporated frequency-based techniques into deep learning models, leading to notable improvements in accuracy and efficiency for time series…
LiNo: Advancing Recursive Residual Decomposition of Linear and Nonlinear Patterns for Robust Time Series Forecasting
Guoqi Yu, Yaoming Li, Xiaoyu Guo +4
Forecasting models are pivotal in a data-driven world with vast volumes of time series data that appear as a compound of vast Linear and Nonlinear patterns. Recent deep time series…