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Zhemeng Yu

4 accepted papers

2026

GKD-Recruiter: Jointly Modeling Social and Task Heterogeneity for Spatial Crowdsourcing via Graph Knowledge Distillation

ICML 2026poster

Social recruitment offers a solution to worker scarcity in Spatial Crowdsourcing (SC) but faces challenges that are often ignored in traditional Influence Maximization. First, task heterogeneity arising from offline execution constraints breaks the ``interest-implies-participation'' assumption, as s…

Cited by 0SourceScholar
2026

JointScaler: A Hierarchical Multi-Indicator Distribution Forecasting Approach for Uncertainty-Aware Joint Scaling in Cloud Services

IJCAI 2026

Proactive scaling improves cloud resource efficiency by forecasting system-relevant indicators and dynamically provisioning resources to maximize utilization while satisfying quality requirements. Existing approaches forecast service indicators in isolation, ignore forecasting uncertainty, and scale

Cited by 0Scholar
2026

POINTS-Long: Adaptive Dual-Mode Visual Reasoning in MLLMs

CVPR 2026

Multimodal Large Language Models (MLLMs) have recently demonstrated remarkable capabilities in cross-modal understanding and generation. However, the rapid growth of visual token sequences--especially in long-video and streaming scenarios--poses a major challenge to their scalability and real-world

Cited by 0SourcecodeScholar
2025

FOLDER: Accelerating Multi-Modal Large Language Models with Enhanced Performance

ICCV 2025poster

Recently, Multi-modal Large Language Models (MLLMs) have shown remarkable effectiveness for multi-modal tasks due to their ability of cross-modal understanding. However, processing long sequences of visual tokens extracted from visual backbones poses challenges for deployment in real-time applicatio…