collaborators

6 papers

cs.LG2026

SPA-Cache: Singular Proxies for Adaptive Caching in Diffusion Language Models

Wenhao Sun, Rong-Cheng Tu, Yifu Ding +4

While Diffusion Language Models (DLMs) offer a flexible, arbitrary-order alternative to the autoregressive paradigm, their non-causal nature precludes standard KV caching, forcing…

cs.CV2025

VORTA: Efficient Video Diffusion via Routing Sparse Attention

Wenhao Sun, Rong-Cheng Tu, Yifu Ding +4

Video diffusion transformers have achieved remarkable progress in high-quality video generation, but remain computationally expensive due to the quadratic complexity of attention o…

cs.CV2025

AD-FM: Multimodal LLMs for Anomaly Detection via Multi-Stage Reasoning and Fine-Grained Reward Optimization

Jingyi Liao, Yongyi Su, Rong-Cheng Tu +6

While Multimodal Large Language Models (MLLMs) demonstrate remarkable capabilities across diverse domains, their application to specialized anomaly detection (AD) remains constrain…

cs.CV2025

SPAZER: Spatial-Semantic Progressive Reasoning Agent for Zero-shot 3D Visual Grounding

Zhao Jin, Rong-Cheng Tu, Jingyi Liao +4

3D Visual Grounding (3DVG) aims to localize target objects within a 3D scene based on natural language queries. To alleviate the reliance on costly 3D training data, recent studies…

cs.CV2025

MLLM-Guided VLM Fine-Tuning with Joint Inference for Zero-Shot Composed Image Retrieval

Rong-Cheng Tu, Zhao Jin, Jingyi Liao +4

Existing Zero-Shot Composed Image Retrieval (ZS-CIR) methods typically train adapters that convert reference images into pseudo-text tokens, which are concatenated with the modifyi…

cs.CV2025

AsymRnR: Video Diffusion Transformers Acceleration with Asymmetric Reduction and Restoration

Wenhao Sun, Rong-Cheng Tu, Jingyi Liao +2

Diffusion Transformers (DiTs) have proven effective in generating high-quality videos but are hindered by high computational costs. Existing video DiT sampling acceleration methods…