8 papers
CFMS: A Coarse-to-Fine Multimodal Synthesis Framework for Enhanced Tabular Reasoning
Qixian Huang, Hongqiang Lin, Tong Fu +5
Reasoning over tabular data is a crucial capability for tasks like question answering and fact verification, as it requires models to comprehend both free-form questions and semi-s…
PointRFT: Explicit Reinforcement Fine-tuning for Point Cloud Few-shot Learning
Yankai Wang, Yiding Sun, Qirui Wang +3
Understanding spatial dynamics and semantics in point cloud is fundamental for comprehensive 3D comprehension. While reinforcement learning algorithms such as Group Relative Policy…
PersonalQ: Select, Quantize, and Serve Personalized Diffusion Models for Efficient Inference
Qirui Wang, Qi Guo, Yiding Sun +4
Personalized text-to-image generation lets users fine-tune diffusion models into repositories of concept-specific checkpoints, but serving these repositories efficiently is difficu…
CMHANet: A Cross-Modal Hybrid Attention Network for Point Cloud Registration
Dongxu Zhang, Yingsen Wang, Yiding Sun +3
Robust point cloud registration is a fundamental task in 3D computer vision and geometric deep learning, essential for applications such as large-scale 3D reconstruction, augmented…
IGASA: Integrated Geometry-Aware and Skip-Attention Modules for Enhanced Point Cloud Registration
Dongxu Zhang, Jihua Zhu, Shiqi Li +4
Point cloud registration (PCR) is a fundamental task in 3D vision and provides essential support for applications such as autonomous driving, robotics, and environmental modeling.…
Not All Queries Need Deep Thought: CoFiCot for Adaptive Coarse-to-fine Stateful Refinement
Dongxu Zhang, Hongqiang Lin, Yiding Sun +4
Scaling test-time computation enhances LLM reasoning ability but faces a uniform computation paradox. Allocating identical resources leads to over-correction on simple tasks and in…