9 papers
VTC-R1: Vision-Text Compression for Efficient Long-Context Reasoning
Yibo Wang, Yongcheng Jing, Shunyu Liu +5
Long-context reasoning has significantly empowered large language models (LLMs) to tackle complex tasks, yet it introduces severe efficiency bottlenecks due to the computational co…
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…
Intra-Trajectory Consistency for Reward Modeling
Chaoyang Zhou, Shunyu Liu, Zengmao Wang +4
Reward models are critical for improving large language models (LLMs), particularly in reinforcement learning from human feedback (RLHF) or inference-time verification. Current rew…
Multimodal Reasoning Agent for Zero-Shot Composed Image Retrieval
Rong-Cheng Tu, Wenhao Sun, Hanzhe You +4
Zero-Shot Composed Image Retrieval (ZS-CIR) aims to retrieve target images given a compositional query, consisting of a reference image and a modifying text-without relying on anno…
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…
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…