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Why On-Policy Distillation Sometimes Fails: Vanishing Learning Signals
Lei Zhao, Qichao Zhao, Bowen Zuo +1
On-policy distillation (OPD) enables effective capability transfer between language models, yet the mechanisms underlying its failures are not fully understood. Across code generat…
Exploring More, Reasoning Better: Stepwise Risk-Sensitive GRPO for Diffusion Language Models
Yue Yu, Yue YU, Bowen Zuo +3
Diffusion large language models (dLLMs) generate text by denoising a sequence or successive blocks, allowing several tokens to be revealed in parallel. Reinforcement learning with…
UniEvo-VL: An On-policy Self-Distillation Training Recipe for Multimodal Model Self-improvement
Fang Wu, Da Xing, Yanjie Huang +16
Modern multimodal models bring generation and understanding into a single unified system, which enables them to provide and learn from their own feedback. Motivated by this unified…
Adaptive Test-Time Compute Allocation with Evolving In-Context Demonstrations
Bowen Zuo, Dongruo Zhou, Yinglun Zhu
While scaling test-time compute can substantially improve model performance, existing approaches either rely on static compute allocation or sample from fixed generation distributi…