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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.CV2026
LLaDA-o: An Effective and Length-Adaptive Omni Diffusion Model
Zebin You, Xiaolu Zhang, Jun Zhou +2
We present \textbf{LLaDA-o}, an effective and length-adaptive omni diffusion model for multimodal understanding and generation. LLaDA-o is built on a Mixture of Diffusion (MoD) fra…
cs.LG2026
Spherical Steering: Geometry-Aware Activation Rotation for Language Models
Zejia You, Chunyuan Deng, Hanjie Chen
Inference-time steering offers a promising way to control language models (LMs) without retraining. However, standard approaches typically rely on activation addition, which inevit…