AuthEval is introduced, a logging and evaluation framework that records both actions, scores the selected action under declared local criteria, and, where feasible, scores the declined proposal under the same rule, and clarifies whether a study's records support claims about the model, the workflow, or both.
Flint Xiaofeng Fan, Cheston Tan, Y. Ong et al.· 0 citations
This paper investigates integrating evolutionary multitasking with Edge Assembly Crossover (MT-EAX) to solve the classical Travelling Salesperson Problem and demonstrates that the advantage of MT-EAX derives from increased diversity through parallel search in early generations, which can be successfully preserved using...
L. Wigney, Aneta Neumann, Y. Ong et al.· Parallel Problem Solving fro...· 0 citations
This paper presents EvTrajGS, an accurate and efficient 3D Gaussian Splatting framework for unposed event streams that enables reliable joint pose-scene optimization initialized from coarse pose priors, eliminating the need for computationally expensive SLAM-style pipelines.
Zixuan Chen, Jiakai Zhang, Junhao Dong et al.· 0 citations
This work proposes a multiagent belief state computation method termed mutual awareness belief (MAB), which extends belief modeling to decentralized partially observable settings by incorporating agents' behavioral intentions and collaborative relationships and proves effective in the nonmonotonic Pursuit environment.
Si-Han Zhou, Tian-Tian He, Yi-Nan Guo et al.· IEEE Transactions on Neural...· 0 citations
Accurate and efficient simulation of edge plasma turbulence is critical for predicting confinement in fusion devices, yet Direct Numerical Simulations (DNS) remain computationally expensive. To address this bottleneck, we present a physics-informed data-driven closure scheme demonstrated on the Hasegawa-Wakatani (HW)...
Kun-Peng Li, Youngwoo Cho, X. Garbet et al.· Plasma Science and Technolog...· 0 citations
A collaborative adversarial fine-tuning framework that maintains multiple experts during training, enables knowledge exchange through embedding-space harmonization, and consolidates the learned knowledge into a single unified robust model.
Nguyen Duc Thai, Junhao Dong, Sua Qi Rong et al.· arXiv.org· 0 citations
FedPref lets institutions with unequal, unpooled data benefit from collaboration without ever sharing reports or annotations, and frozen public language models propose alternative JSON extractions, local annotations rank them, and sites collaboratively train compact Qwen3-8B adapters while sharing only model updates.
Flint Xiaofeng Fan, Cheston Tan, Y. Ong et al.· 0 citations
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