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Home/Authors/Che Liu

Che Liu

2 indexed papers

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

Publications per year

2
26

Top categories

AI×2Vision×1ML×1

Frequent co-authors

Haozhe Wang1×
Weijia Feng1×
Jinpeng Yu1×
Ping Nie1×
Fangzhen Lin1×
Jiaming 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.

Search Beyond What Can Be Taught: Evolving the Knowledge Boundary in Agentic Visual Generation

The paper constructs datasets and benchmarks to evaluate the performance of visual generators in handling open-ended requests, and proposes a teach-then-search co-training framework to improve their world-knowledge.

Highlighted terms show continued research focus across papers

Papers

cs.CVcs.AIEmpiricalRecentJul 6, 2026

Search Beyond What Can Be Taught: Evolving the Knowledge Boundary in Agentic Visual Generation

Haozhe Wang, Weijia Feng, Jinpeng Yu, Che Liu +7 more

The paper constructs datasets and benchmarks to evaluate the performance of visual generators in handling open-ended requests, and proposes a teach-then-search co-training framework to improve their w…

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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 →