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Home/Authors/Fang Zhao

Fang Zhao

2 indexed papers

Recent (6 mo)
2
With code
0
Influential cites
0
Benchmarked
0

Publications per year

2
26

Top categories

Software Eng.×1NLP×1ML×1AI×1

Frequent co-authors

Shiguo Lian1×
Kai Wang1×
Zhaoxiang Liu1×
Wen Liu1×
Minjie Hua1×
Yutong Liu1×

Research Timeline

2026
GDSD: Reinforcement Learning as Guided Denoiser Self-Distillation for Diffusion Language Models

The paper proposes Guided Denoiser Self-Distillation (GDSD), a novel method that bypasses the use of likelihood surrogates (like ELBO) in RL for diffusion language models, achieving state-of-the-art performance on complex benchmarks.

Token-Operations-Oriented Inference Optimization Techniques for Large Models

This paper proposes a four-layer technical architecture for large model inference optimization, including Multi-model Fusion, Model Optimization, Compute-Model Fusion, and Compute-Network-Model Fusion.

Highlighted terms show continued research focus across papers

Papers

cs.SEcs.CLSurveyRecentJun 18, 2026

Token-Operations-Oriented Inference Optimization Techniques for Large Models

Shiguo Lian, Kai Wang, Zhaoxiang Liu, Wen Liu +21 more

This paper proposes a four-layer technical architecture for large model inference optimization, including Multi-model Fusion, Model Optimization, Compute-Model Fusion, and Compute-Network-Model Fusion…

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cs.LGcs.AIRecent
May 28, 2026

GDSD: Reinforcement Learning as Guided Denoiser Self-Distillation for Diffusion Language Models

Xiaohang Tang, Keyue Jiang, Che Liu, Qifang Zhao +3 more

The paper proposes Guided Denoiser Self-Distillation (GDSD), a novel method that bypasses the use of likelihood surrogates (like ELBO) in RL for diffusion language models, achieving state-of-the-art p…

View →