---
title: "Who cites Shen Nie — 208 papers of our library"
description: "208 papers of the Elamur Research library cite the works of Shen Nie, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/shen-nie/cited-by/"
---
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# Who cites Shen Nie

250 citations of their works from 208 papers of our library (of the 149,439 whose bibliographies we read) · 55 with a page here, the most cited first · [← Shen Nie](https://md.research.elamur.ai/free/en/authors/shen-nie/)

1. [**Wan: Open and Advanced Large-Scale Video Generative Models arXiv:2503.20314**Team Wan, Ang Wang, Baole Ai, et al.*2025 · 260 citations*](https://md.research.elamur.ai/free/en/papers/wan-2025-wan-open-advanced-large-scale/)
2. **[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*
3. [**HunyuanVideo: A Systematic Framework For Large Video Generative Models arXiv:2412.03603**Weijie Kong, Qi Tian, Zijian Zhang, et al.*2024 · 169 citations*](https://md.research.elamur.ai/free/en/papers/kong-2024-hunyuanvideo-systematic-framework-large/)
4. [**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/)
5. [**PixArt-α: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis arXiv:2310.00426**Junsong Chen, Jincheng Yu, Chongjian Ge, et al.*2023 · 87 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-pixart-alpha-fast-training-diffusion/)
6. **[SageAttention: Accurate 8-Bit Attention for Plug-and-play Inference Acceleration](https://md.research.elamur.ai/free/en/papers/zhang-2024-sageattention-accurate-8-bit-attention/) [International Conference on Learning Representations (ICLR)](https://md.research.elamur.ai/free/en/venues/international-conference-on-learning-representations-iclr/)**Jintao Zhang, Jia Wei, Haofeng Huang, et al.*2024 · 74 citations*
7. [**A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and Beyond arXiv:2503.21614**Xiaoye Qu, Yafu Li, Zhao-Chen Su, et al.*2025 · 55 citations*](https://md.research.elamur.ai/free/en/papers/qu-2025-survey-efficient-reasoning-large-reasoning/)
8. **[JanusFlow: Harmonizing Autoregression and Rectified Flow for Unified Multimodal Understanding and Generation](https://md.research.elamur.ai/free/en/papers/ma-2024-janusflow-harmonizing-autoregression-rectified/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Yiyang Ma, Xingchao Liu, Xiaokang Chen, et al.*2024 · 52 citations*
9. **[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*
10. [**Hunyuan-DiT: A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding arXiv:2405.08748**Zhimin Li, Jianwei Zhang, Qin Lin, et al.*2024 · 35 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-hunyuan-dit-powerful-multi/)
11. [**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/)
12. [**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/)
13. [**When To Solve, When To Verify: Compute-Optimal Problem Solving and Generative Verification for LLM Reasoning arXiv:2504.01005**Nishad Singhi, Hritik Bansal, Arian Hosseini, et al.*2025 · 12 citations*](https://md.research.elamur.ai/free/en/papers/singhi-2025-solve-verify-compute-optimal-problem/)
14. **[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*
15. **[TESS 2: A Large-Scale Generalist Diffusion Language Model](https://md.research.elamur.ai/free/en/papers/tae-2025-tess-2-large-scale-generalist/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jaesung Tae, Hamish Ivison, Sachin Kumar, et al.*2025 · 9 citations*
16. **[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*
17. **[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*
18. **[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*
19. **[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*
20. **[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*
21. **[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*
22. **[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*
23. **[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*
24. **[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*
25. **[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*
26. **[Transforming Causal LLM into MLM Encoder for Detecting Social Media Manipulation in Telegram](https://md.research.elamur.ai/free/en/papers/bazdyrev-2025-transforming-causal-llm-into-mlm/) [Ukrainian Natural Language Processing Workshop](https://md.research.elamur.ai/free/en/venues/unlp/)**Anton Bazdyrev, Ivan Bashtovyi, Ivan Havlytskyi, et al.*2025 · 2 citations*
27. **[Diffuse Thinking: Exploring Diffusion Language Models as Efficient Thought Proposers for Reasoning](https://md.research.elamur.ai/free/en/papers/shao-2026-diffuse-thinking-exploring-diffusion-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chenyang Shao, Sijian Ren, Fengli Xu, et al.*2026 · 1 citation*
28. **[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*
29. **[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*
30. **[Energy Matching based Preference Learning for Diffusion Language Models](https://md.research.elamur.ai/free/en/papers/shankar-2026-energy-matching-based-preference-learning/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Shiv Shankar*2026 · 1 citation*
31. **[From Static Inference to Dynamic Interaction: A Survey of Streaming Large Language Models](https://md.research.elamur.ai/free/en/papers/tong-2026-static-inference-dynamic-interaction-survey/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Junlong Tong, Zilong Wang, YuJie Ren, et al.*2026 · 1 citation*
32. **[A Universal Avoidance Method for Diverse Multi-branch Generation](https://md.research.elamur.ai/free/en/papers/park-2026-universal-avoidance-method-diverse-multi/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kyeongman Park, Minha Jhang, Kyomin Jung*2026*
33. **[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*
34. **[Amadeus: Autoregressive Model with Bidirectional Attribute Modelling for Symbolic Music](https://md.research.elamur.ai/free/en/papers/su-2026-amadeus-autoregressive-model-bidirectional-attribute/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hongju Su, Ke Li, Lan Yang, et al.*2026*
35. **[BiMol-Diff: A Unified Diffusion Framework for Molecular Generation and Captioning](https://md.research.elamur.ai/free/en/papers/shahane-2026-bimol-diff-unified-diffusion-framework/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Aditya Hemant Shahane, Anuj Kumar Sirohi, Devansh Arora, et al.*2026*
36. **[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*
37. **[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*
38. **[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*
39. **[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*
40. **[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*
41. **[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*
42. **[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*
43. **[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*
44. **[Fixing Semantic Blind Spots in Anchor Tokens of dMLLMs](https://md.research.elamur.ai/free/en/papers/xu-2026-fixing-semantic-blind-spots-anchor/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ruixuan Xu, Jiexi Xu, Qiyan Zhao, et al.*2026*
45. **[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*
46. **[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*
47. **[Memorization, Emergence, and Explaining Reversal Failures: A Controlled Study of Relational Semantics in LLMs](https://md.research.elamur.ai/free/en/papers/zhu-2026-memorization-emergence-explaining-reversal-failures/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yihua Zhu, Qianying Liu, Jiaxin Wang, et al.*2026*
48. **[Multimodal Large Language Models for Multi-Subject In-Context Image Generation](https://md.research.elamur.ai/free/en/papers/zhou-2026-multimodal-large-language-models-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yucheng Zhou, Dubing Chen, Huan Zheng, et al.*2026*
49. **[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*
50. **[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*
51. **[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*
52. **[SpecBound: Adaptive Bounded Self-Speculation with Layer-wise Confidence Calibration](https://md.research.elamur.ai/free/en/papers/wen-2026-specbound-adaptive-bounded-self-speculation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhuofan Wen, Yang Feng*2026*
53. **[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*
54. **[UniCM: A Unified Consistency Model For Efficient Multimodal Generation and Understanding](https://md.research.elamur.ai/free/en/papers/xu-2026-unicm-unified-consistency-model-efficient/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chenkai Xu, Xu Wang, Zhenyi Liao, et al.*2026*
55. **[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*

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

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