Author

Fengran Mo

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#artificial intelligence Preprint Sep 2026

SIPO: Unifying Reinforcement Learning with On-Policy Self-Distillation

Reinforcement learning with verifiable rewards (RLVR) has become a standard paradigm for improving large language models (LLMs) on various tasks, yet its sparse outcome rewards lack token-level credit assignment for intermediate steps. To address this, on-policy self-distillation (OPSD) leverages a self-teacher with pr...

Zhenrui Yue, Hui-Min Zeng, Yue-Qi Wang et al. · 0 citations

Jul 2026

Discrete Diffusion Models: A Unified Framework from Tokenization to Generation

This work introduces a unified conceptual framework that views discrete diffusion models through the construction of the underlying discrete state space, and exposes common design trade-offs across training objectives, inference algorithms, scaling behavior, systems optimization, and evaluation protocols.

Ye Yuan, Wei-En Li, Rui Song et al. · arXiv.org · 0 citations