8 papers
Learning to Label: A Reinforced Self-Evolving Framework for Semi-supervised Referring Expression Segmentation
Runlong Cao, Ying Zang, Chuanwei Zhou +4
Semi-supervised referring expression segmentation (SS-RES) aims to achieve precise pixel-level language grounding under limited annotation, yet suffers from limited supervision and…
High-level hadronic tau lepton triggers of the CMS experiment in proton-proton collisions at = 13.6 TeV
CMS Collaboration
The trigger system of the CMS detector is pivotal in the acquisition of data for physics measurements and searches. Studies of final states characterized by hadronic decays of tau…
StarCraft+: Benchmarking Multi-agent Algorithms in Adversary Paradigm
Yadong Li, Tong Zhang, Bo Huang +1
Deep multi-agent reinforcement learning (MARL) algorithms are booming in the field of collaborative intelligence, and StarCraft multi-agent challenge (SMAC) is widely-used as the b…
GraphTorque: Torque-Driven Rewiring Graph Neural Network
Sujia Huang, Lele Fu, Zhen Cui +3
Graph Neural Networks (GNNs) have emerged as powerful tools for learning from graph-structured data, leveraging message passing to diffuse information and update node representatio…
Distribution Prototype Diffusion Learning for Open-set Supervised Anomaly Detection
Fuyun Wang, Tong Zhang, Yuanzhi Wang +4
In Open-set Supervised Anomaly Detection (OSAD), the existing methods typically generate pseudo anomalies to compensate for the scarcity of observed anomaly samples, while overlook…
Strictly monotone mean-variance preferences with applications to portfolio selection
Yike Wang, Yusha Chen, Jingzhen Liu +1
The monotone mean-variance (MMV) preference proposed by Maccheroni, et al. (Math. Finance 19(3): 487-521, 2009) fails to differentiate strictly dominant payoffs, which may cause in…
MPDS: A Movie Posters Dataset for Image Generation with Diffusion Model
Meng Xu, Tong Zhang, Fuyun Wang +3
Movie posters are vital for captivating audiences, conveying themes, and driving market competition in the film industry. While traditional designs are laborious, intelligent gener…
UniKG: A Benchmark and Universal Embedding for Large-Scale Knowledge Graphs
Yide Qiu, Shaoxiang Ling, Tong Zhang +2
Irregular data in real-world are usually organized as heterogeneous graphs (HGs) consisting of multiple types of nodes and edges. To explore useful knowledge from real-world data,…