Papers by Junlin Zhu
Parallelism and Generation Order in Masked Diffusion Language Models: Limits Today, Potential Tomorrow (2026.findings-acl)
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Yangyang Zhong, Yanmei Gu, Zhengqing Zang, Xiaomeng Li, Yuqi Ding, Xibei Jia, Yuting Shen, Zhenzhong Lan, Liwang Zhu, Weiping Liu, Junlin Zhou, Haisheng Liu, Zhong Xin Yu, Pengxin Luo, Donglian Qi, Yunfeng Yan, Junbo Zhao
| Challenge: | Autoregressive (AR) language models dominate modern natural language processing due to strong likelihood-based training objectives and reliable left-to-right decoding. |
| Approach: | They characterize MDLM behavior along two dimensions: parallelism strength and generation order . authors propose a Generate-then-Edit paradigm that mitigates dependency loss . |
| Outcome: | The proposed model improves on tasks that require "backward information" the Generate-then-Edit paradigm improves parallel decoding efficiency while reducing dependency loss. |
QuantileMark: A Message-Symmetric Multi-bit Watermark for LLMs (2026.acl-long)
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| Challenge: | a number of large language models (LLMs) require multi-bit watermarking to ensure provenance. |
| Approach: | They propose a multi-bit watermark that embeds messages within a continuous cumulative probability interval. |
| Outcome: | The proposed watermark breaks message symmetry in low-entropy decoding, showing it can be used for verification and quality verification. |