5 papers
Align then Adapt: Rethinking Parameter-Efficient Transfer Learning in 4D Perception
Yiding Sun, Jihua Zhu, Haozhe Cheng +4
Point cloud video understanding is critical for robotics as it accurately encodes motion and scene interaction. We recognize that 4D datasets are far scarcer than 3D ones, which ha…
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…
TikArt: Stabilizing Aperture-Guided Fine-Grained Visual Reasoning with Reinforcement Learning
Hao Ding, Zhichuan Yang, Weijie Ge +3
Fine-grained visual reasoning in multimodal large language models (MLLMs) is bottlenecked by single-pass global image encoding: key evidence often lies in tiny objects, cluttered r…
AFBS:Buffer Gradient Selection in Semi-asynchronous Federated Learning
Chaoyi Lu, Yiding Sun, Jinqian Chen +3
Asynchronous federated learning (AFL) accelerates training by eliminating the need to wait for stragglers, but its asynchronous nature introduces gradient staleness, where outdated…
Corrected with the Latest Version: Make Robust Asynchronous Federated Learning Possible
Chaoyi Lu, Yiding Sun, Pengbo Li +1
As an emerging paradigm of federated learning, asynchronous federated learning offers significant speed advantages over traditional synchronous federated learning. Unlike synchrono…