4 citations · 11 across the 19 of their papers we have counts for
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cs.AI2026
LLaDA MoE v2: Scaling Mixture-of-Experts Diffusion Language Models
Fengqi Zhu, Shaoxuan Xu, Jingyang Ou +11
Diffusion language models (dLLMs) offer an alternative to autoregressive (AR) language modeling, yet the scaling behavior of Mixture-of-Experts (MoE) dLLMs remains poorly understoo…
cs.AI2026
DLLM-Searcher: Adapting Diffusion Large Language Model for Search Agents
Jiahao Zhao, Shaoxuan Xu, Zhongxiang Sun +6
Recently, Diffusion Large Language Models (dLLMs) have demonstrated unique efficiency advantages, enabled by their inherently parallel decoding mechanism and flexible generation pa…
cs.AI2024★ 1 cited
Scaling up Masked Diffusion Models on Text
Shen Nie, Fengqi Zhu, Chao Du +5
Masked diffusion models (MDMs) have shown promise in language modeling, yet their scalability and effectiveness in core language tasks, such as text generation and language underst…