6 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…
Beyond Prompt: Fine-grained Simulation of Cognitively Impaired Standardized Patients via Stochastic Steering
Weikang Zhang, Zimo Zhu, Zhichuan Yang +3
Simulating Standardized Patients with cognitive impairment offers a scalable and ethical solution for clinical training. However, existing methods rely on discrete prompt engineeri…
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…
FedPSA: Modeling Behavioral Staleness in Asynchronous Federated Learning
Chaoyi Lu, Yiding Sun, Zhichuan Yang +3
Asynchronous Federated Learning (AFL) has emerged as a significant research area in recent years. By not waiting for slower clients and executing the training process concurrently,…
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by eliminating the need to wait for stragglers, but its asynchronous nature introduces gradient staleness, where outdated…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…