الباحثون

Yang You

المنشورات 2

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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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Loop Dropout: Regularizing Shared Updates in Looped Language Models

Zirui Zhu, Hailun Xu, Xuanlei Zhao وآخرون · 2026

Looped language models separate computational depth from parameter count by repeatedly applying the same transformer block. Adapting these models requires a shared update that remains effective as hidden states evolve throughout the recurrent computation. Our empirical analysis reveals a pronounced late-loop bias in st …

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