---
title: "Who cites Dream 7B: Diffusion Large Language Models"
description: "88 papers of the Elamur Research library cite «Dream 7B: Diffusion Large Language Models», found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/papers/ye-2025-dream-7b-diffusion-large-language/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Dream 7B: Diffusion Large Language Models](https://md.research.elamur.ai/free/en/papers/ye-2025-dream-7b-diffusion-large-language/) / cited by

# Who cites «Dream 7B: Diffusion Large Language Models»

88 papers of our library cite it (of the 149,439 whose bibliographies we read) · 24 with a page here, the most cited first · [← back to «Dream 7B: Diffusion Large Language Models»](https://md.research.elamur.ai/free/en/papers/ye-2025-dream-7b-diffusion-large-language/)

1. **[Attention Sinks in Diffusion Language Models](https://md.research.elamur.ai/free/en/papers/rulli-2026-attention-sinks-diffusion-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Maximo Eduardo Rulli, Simone Petruzzi, Edoardo Michielon, et al.*2026 · 5 citations*
2. **[d-TreeRPO: Towards More Reliable Policy Optimization for Diffusion Language Models](https://md.research.elamur.ai/free/en/papers/pan-2026-d-treerpo-more-reliable-policy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Leyi Pan, Shuchang Tao, Yunpeng Zhai, et al.*2026 · 3 citations*
3. **[dLLM: Simple Diffusion Language Modeling](https://md.research.elamur.ai/free/en/papers/zhou-2026-dllm-simple-diffusion-language-modeling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhanhui Zhou, Lingjie Chen, Hanghang Tong, et al.*2026 · 3 citations*
4. **[Beyond Hard Masks: Progressive Token Evolution for Diffusion Language Models](https://md.research.elamur.ai/free/en/papers/zhong-2026-beyond-hard-masks-progressive-token/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Linhao Zhong, Linyu Wu, Bozhen Fang, et al.*2026 · 2 citations*
5. **[Focus-dLLM: Accelerating Long-Context Diffusion LLM Inference via Confidence-Guided Context Focusing](https://md.research.elamur.ai/free/en/papers/long-2026-focus-dllm-accelerating-long-context/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lingkun Long, Yushi Huang, Shihao Bai, et al.*2026 · 2 citations*
6. **[Improving the Throughput of Diffusion-based Large Language Models via a Training-Free Confidence-Aware Calibration](https://md.research.elamur.ai/free/en/papers/shen-2026-improving-throughput-diffusion-based-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jucheng Shen, Gaurav Sarkar, Yeonju Ro, et al.*2026 · 2 citations*
7. **[LADR: Locality-Aware Dynamic Rescue for Efficient Text-to-Image Generation with Diffusion Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-ladr-locality-aware-dynamic-rescue/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chenglin Wang, Yucheng Zhou, Shuang Chen, et al.*2026 · 2 citations*
8. **[One Token Is Enough: Improving Diffusion Language Models with a Sink Token](https://md.research.elamur.ai/free/en/papers/zhang-2026-one-token-is-enough-improving/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zihou Zhang, Zheyong Xie, Li Zhong, et al.*2026 · 2 citations*
9. **[Diffusion-CAM: Faithful Visual Explanations for dMLLMs](https://md.research.elamur.ai/free/en/papers/zuo-2026-diffusion-cam-faithful-visual-explanations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haomin Zuo, Yidi Li, Luoxiao Yang, et al.*2026 · 1 citation*
10. **[Efficient Self-Evaluation for Diffusion Language Models via Sequence Regeneration](https://md.research.elamur.ai/free/en/papers/zhong-2026-efficient-self-evaluation-diffusion-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Linhao Zhong, Linyu Wu, Wen Wang, et al.*2026 · 1 citation*
11. **[Advancing Reasoning in Diffusion Language Models with Denoising Process Rewards](https://md.research.elamur.ai/free/en/papers/xie-2026-advancing-reasoning-diffusion-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shaoan Xie, Lingjing Kong, Xiangchen Song, et al.*2026*
12. **[Breaking Block Boundaries: Anchor-based History-stable Decoding for Diffusion Large Language Models](https://md.research.elamur.ai/free/en/papers/zou-2026-breaking-block-boundaries-anchor-based/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shun Zou, Yong Wang, Zehui Chen, et al.*2026*
13. **[CreditDecoding: Accelerating Parallel Decoding in Diffusion Large Language Models with Trace Credit](https://md.research.elamur.ai/free/en/papers/wang-2026-creditdecoding-accelerating-parallel-decoding-diffusion/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kangyu Wang, Zhiyun Jiang, Haibo Feng, et al.*2026*
14. **[DecoCal: Decoding with Calibration in Diffusion Large Language Models](https://md.research.elamur.ai/free/en/papers/xu-2026-decocal-decoding-calibration-diffusion-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fan Xu, Huixuan Zhang, Xiaojun Wan*2026*
15. **[Diff4TST: Masked Diffusion Language Model for Text Style Transfer](https://md.research.elamur.ai/free/en/papers/ma-2026-diff4tst-masked-diffusion-language-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinchen Ma, Gaole He, Yunshi Lan, et al.*2026*
16. **[Diffusion with Truncated Blocks: Fast and High-Quality Text Generation using Truncated Block Generation](https://md.research.elamur.ai/free/en/papers/zhou-2026-diffusion-truncated-blocks-fast-high/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuyan Zhou, Weiyu Chen, James Kwok*2026*
17. **[DOS: Dependency-Oriented Sampler for Masked Diffusion Language Models](https://md.research.elamur.ai/free/en/papers/zhou-2026-dos-dependency-oriented-sampler-masked/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xueyu Zhou, Yangrong Hu, Jian Huang*2026*
18. **[Fast-Decoding Diffusion Language Models via Progress-Aware Confidence Schedules](https://md.research.elamur.ai/free/en/papers/mohamed-2026-fast-decoding-diffusion-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Amr Mohamed, Yang Zhang, Michalis Vazirgiannis, et al.*2026*
19. **[From AR to Diffusion: Efficiently Adapting Large Language Models with Strictly Causal and Elastic Horizons](https://md.research.elamur.ai/free/en/papers/ma-2026-ar-diffusion-efficiently-adapting-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiangyu Ma, Teng Xiao, Zuchao Li, et al.*2026*
20. **[Parallelism and Generation Order in Masked Diffusion Language Models: Limits Today, Potential Tomorrow](https://md.research.elamur.ai/free/en/papers/zhong-2026-parallelism-generation-order-masked-diffusion/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yangyang Zhong, Yanmei Gu, Zhengqing Zang, et al.*2026*
21. **[PURE: Post-hoc Unlocking and REfinement for Discrete Diffusion Decoding](https://md.research.elamur.ai/free/en/papers/park-2026-pure-post-hoc-unlocking-refinement/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yangryeol Park, Kunhui Lee, Hanback Choi, et al.*2026*
22. **[T: Progressive Block Scaling for Masked Diffusion Language Models Through Trajectory Aware Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/xia-2026-t-star-progressive-block-scaling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hanchen Xia, Baoyou Chen, Yutang Ge, et al.*2026*
23. **[The Bitter Lesson of Diffusion Language Models for Agentic Workflows: A Comprehensive Reality Check](https://md.research.elamur.ai/free/en/papers/lu-2026-bitter-lesson-diffusion-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qingyu Lu, Liang Ding, Kanjian Zhang, et al.*2026*
24. **[You Can Have a Second Chance: Unbiased and Multi-bit Watermarking for Diffusion Language Models with Regret-based Remasking](https://md.research.elamur.ai/free/en/papers/yang-2026-you-can-have-second-chance/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ke Yang, Dongyang Liang, Jing Yu, et al.*2026*

64 more papers of our library cite it; they have no page here yet.

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