الباحثون

Geng Zhang

المنشورات 2

نسخة أولية وصول مفتوح

DivMoE: Fine-Grained MoE Upcycling via Cross-Domain Expert Composition

Yuxuan Lou, Kai Yang, Geng Zhang وآخرون · 2026

Mixture-of-Experts (MoE) architectures have become essential for scaling large language models, with recent work demonstrating the benefits of fine-grained expert designs. Training such models from scratch is expensive, and sparse upcycling from pre-trained dense models is an attractive alternative. However, we identif …

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Calibrating Retrieval Geometry: Reliability-Guided Training-Free Aggregation for Visual Place Recognition

Xin Li, Zhimin Mao, Shang Wang وآخرون · 2026

Frozen visual foundation models provide transferable features for visual place recognition, but fixed aggregation can suppress useful distinctions in new environments. We introduce TFA, a reliability-guided, training-free aggregation method requiring neither place labels nor task-specific weight updates. Our key observ …

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