3 citations · 3 across the 4 of their papers we have counts for
8 papers
Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models
Siyan Zhao, Zhihui Xie, Mengchen Liu +4
Knowledge distillation improves large language model (LLM) reasoning by compressing the knowledge of a teacher LLM to train smaller LLMs. On-policy distillation advances this appro…
Accelerating Inference of Masked Image Generators via Reinforcement Learning
Pranav Subbaraman, Shufan Li, Siyan Zhao +1
Masked Generative Models (MGM)s demonstrate strong capabilities in generating high-fidelity images. However, they need many sampling steps to create high-quality generations, resul…
SPG: Sandwiched Policy Gradient for Masked Diffusion Language Models
Chenyu Wang, Paria Rashidinejad, DiJia Su +9
Diffusion large language models (dLLMs) are emerging as an efficient alternative to autoregressive models due to their ability to decode multiple tokens in parallel. However, align…
Inpainting-Guided Policy Optimization for Diffusion Large Language Models
Siyan Zhao, Mengchen Liu, Jing Huang +8
Masked diffusion large language models (dLLMs) are emerging as promising alternatives to autoregressive LLMs, offering competitive performance while supporting unique generation ca…
Multi-fidelity Reinforcement Learning Control for Complex Dynamical Systems
Luning Sun, Xin-Yang Liu, Siyan Zhao +3
Controlling instabilities in complex dynamical systems is challenging in scientific and engineering applications. Deep reinforcement learning (DRL) has seen promising results for a…
d1: Scaling Reasoning in Diffusion Large Language Models via Reinforcement Learning
Siyan Zhao, Devaansh Gupta, Qinqing Zheng +1
Recent large language models (LLMs) have demonstrated strong reasoning capabilities that benefits from online reinforcement learning (RL). These capabilities have primarily been de…