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Home/Authors/Molei Tao

Molei Tao

2 indexed papers

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

Publications per year

2
26

Top categories

ML×2Algorithms×1Numerical Analysis×1Probability×1Stats ML×1AI×1

Frequent co-authors

Kijung Jeon1×
Thuy-Duong Vuong1×
Yuchen Zhu1×
Jing Shi1×
Chongjian Ge1×
Hao Tan1×

Research Timeline

2026
FLARE: Diffusion for Hybrid Language Model

FLARE is a systematic conversion framework that enables a single checkpoint to support both autoregressive (AR) and diffusion-style parallel decoding for hybrid-attention large language models, achieving competitive performance and throughput gains.

VGB for Masked Diffusion Model: Efficient Test-time Scaling for Reward Satisfaction and Sample Editing

The paper introduces MDM-VGB, a reward-guided sampler for Masked Diffusion Models, which extends the Jerrum-Sinclair backtracking Markov chain to a masked-state graph for effective high-reward generation and efficient repair of low-reward samples.

Highlighted terms show continued research focus across papers

Papers

cs.LGcs.DSmath.NATheoreticalRecentJun 26, 2026

VGB for Masked Diffusion Model: Efficient Test-time Scaling for Reward Satisfaction and Sample Editing

Kijung Jeon, Thuy-Duong Vuong, Molei Tao

The paper introduces MDM-VGB, a reward-guided sampler for Masked Diffusion Models, which extends the Jerrum-Sinclair backtracking Markov chain to a masked-state graph for effective high-reward generat…

View →
cs.LGcs.AIRecent
Jun 1, 2026

FLARE: Diffusion for Hybrid Language Model

Yuchen Zhu, Jing Shi, Chongjian Ge, Hao Tan +8 more

FLARE is a systematic conversion framework that enables a single checkpoint to support both autoregressive (AR) and diffusion-style parallel decoding for hybrid-attention large language models, achiev…

View →