---
title: "Who cites Marianne Arriola — 108 papers of our library"
description: "108 papers of the Elamur Research library cite the works of Marianne Arriola, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/marianne-arriola/cited-by/"
---
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# Who cites Marianne Arriola

111 citations of their works from 108 papers of our library (of the 149,439 whose bibliographies we read) · 29 with a page here, the most cited first · [← Marianne Arriola](https://md.research.elamur.ai/free/en/authors/marianne-arriola/)

1. **[Large Language Diffusion Models](https://md.research.elamur.ai/free/en/papers/nie-2025-large-language-diffusion-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shen Nie, Fengqi Zhu, Zebin You, et al.*2025 · 178 citations*
2. **[Simplified and Generalized Masked Diffusion for Discrete Data](https://md.research.elamur.ai/free/en/papers/shi-2024-simplified-generalized-masked-diffusion-discrete/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jiaxin Shi, Kehang Han, Zhe Wang, et al.*2024 · 90 citations*
3. [**Dream 7B: Diffusion Large Language Models arXiv:2508.15487**Jiacheng Ye; Zhihui Xie; Lin Zheng; Jiahui Gao; Zirui Wu; Xin Jiang; Zhenguo Li;, Lingpeng Kong*2025 · 89 citations*](https://md.research.elamur.ai/free/en/papers/ye-2025-dream-7b-diffusion-large-language/)
4. **[LLaDA 1.5: Variance-Reduced Preference Optimization for Large Language Diffusion Models](https://md.research.elamur.ai/free/en/papers/zhu-2026-llada-1-5-variance-reduced/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fengqi Zhu, Rongzhen Wang, Shen Nie, et al.*2026 · 49 citations*
5. [**Seed Diffusion: A Large-Scale Diffusion Language Model with High-Speed Inference arXiv:2508.02193**Yuxuan Song, Zheng Zhang, Cheng Luo, et al.*2025 · 28 citations*](https://md.research.elamur.ai/free/en/papers/song-2025-seed-diffusion-large-scale/)
6. [**A Survey on Latent Reasoning arXiv:2507.06203**Rui-Jie Zhu, Tianhao Peng, Tianhao Cheng, et al.*2025 · 15 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-survey-latent-reasoning/)
7. **[Diffusion vs. Autoregressive Language Models: A Text Embedding Perspective](https://md.research.elamur.ai/free/en/papers/zhang-2025-diffusion-vs-autoregressive-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Siyue Zhang, Yilun Zhao, Liyuan Geng, et al.*2025 · 10 citations*
8. [**Beyond Autoregression: Fast LLMs via Self-Distillation Through Time arXiv:2410.21035**Justin Deschenaux, Caglar Gulcehre*2024 · 10 citations*](https://md.research.elamur.ai/free/en/papers/deschenaux-2024-autoregression-fast-llms-self-distillation/)
9. **[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*
10. [**d2: Improving Reasoning in Diffusion Language Models via Trajectory Likelihood Estimation arXiv:2509.21474**Guanghan Wang, Gilad Turok, Yair Schiff, et al.*2025 · 4 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-d2-improving-reasoning-diffusion-language/)
11. **[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*
12. **[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*
13. **[TreeDiff: AST-Guided Code Generation with Diffusion LLMs](https://md.research.elamur.ai/free/en/papers/zeng-2026-treediff-ast-guided-code-generation/) [Workshop on Structured Understanding, Retrieval, and Generation in the LLM Era](https://md.research.elamur.ai/free/en/venues/surgellm/)**Yiming Zeng, Jinghan Cao, Zexin Li, et al.*2026 · 3 citations*
14. **[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*
15. **[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*
16. **[On-Policy Self-Distillation for Efficient Diffusion Language Models with Early-Stage Calibration](https://md.research.elamur.ai/free/en/papers/zhu-2026-policy-self-distillation-efficient-diffusion/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Huaisheng Zhu, MingYu Liu, Junze Liu, et al.*2026 · 2 citations*
17. **[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*
18. **[SpanDiffusion: Flow Matching over Continuous Span Masks for Financial Causal Question Answering](https://md.research.elamur.ai/free/en/papers/niess-2026-spandiffusion-flow-matching-over-continuous/) [Financial Narrative Processing Workshop](https://md.research.elamur.ai/free/en/venues/fnp/)**Georg Niess, Roman Kern*2026 · 1 citation*
19. **[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*
20. **[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*
21. **[DIFFA-2: A Practical Diffusion Large Language Model for General Audio Understanding](https://md.research.elamur.ai/free/en/papers/zhou-2026-diffa-2-practical-diffusion-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiaming Zhou, Xuxin Cheng, Shiwan Zhao, et al.*2026*
22. **[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*
23. **[LR-DWM: Efficient Watermarking for Diffusion Language Models](https://md.research.elamur.ai/free/en/papers/raban-2026-lr-dwm-efficient-watermarking-diffusion/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ofek Raban, Gal Chechik, Ethan Fetaya*2026*
24. **[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*
25. **[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*
26. **[RACC: Regret-Aware Confidence Calibration for Consistent Masked Discrete Diffusion Decoding](https://md.research.elamur.ai/free/en/papers/zeng-2026-racc-regret-aware-confidence-calibration/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qinglin Zeng, Jusheng Zhang, Jing Yang, et al.*2026*
27. **[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*
28. **[xLM: A Python Package for Non-Autoregressive Language Models](https://md.research.elamur.ai/free/en/papers/patel-2026-xlm-python-package-non-autoregressive/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Dhruvesh Patel, Durga Prasad Maram, Sai Sreenivas Chintha, et al.*2026*
29. **[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*

79 more citing papers of our library have no page here yet.

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