---
title: "Who cites Ziheng Jiang — 686 papers of our library"
description: "686 papers of the Elamur Research library cite the works of Ziheng Jiang, found in their bibliographies; the most cited first."
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---
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# Who cites Ziheng Jiang

789 citations of their works from 686 papers of our library (of the 149,439 whose bibliographies we read) · 59 with a page here, the most cited first · [← Ziheng Jiang](https://md.research.elamur.ai/free/en/authors/ziheng-jiang/)

1. **[Transformers: State-of-the-Art Natural Language Processing](https://md.research.elamur.ai/free/en/papers/wolf-2020-transformers-state-art-natural-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Thomas Wolf, Lysandre Debut, Victor Sanh, et al.*2020 · 15,755 citations*
2. [**Longformer: The Long-Document Transformer arXiv:2004.05150**Iz Beltagy, Matthew E. Peters, Arman Cohan*2020 · 3,880 citations*](https://md.research.elamur.ai/free/en/papers/beltagy-2020-longformer-long-document-transformer/)
3. **[PyTorch 2: Faster Machine Learning Through Dynamic Python Bytecode Transformation and Graph Compilation](https://md.research.elamur.ai/free/en/papers/ansel-2024-pytorch-2-faster-machine-learning/) [ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS)](https://md.research.elamur.ai/free/en/venues/acm-international-conference-on-architectural-support-for-programming-languages/)**Jason Ansel, Edward Yang, Horace He, et al.*2024 · 946 citations*
4. [**Triton: An Intermediate Language and Compiler for Tiled Neural Network Computations MAPL 2019**Philippe Tillet, H. T. Kung, David Cox*2019 · 729 citations*](https://md.research.elamur.ai/free/en/papers/tillet-2019-triton-intermediate-language-compiler-tiled/)
5. [**HybridFlow: A Flexible and Efficient RLHF Framework arXiv:2409.19256**Guangming Sheng, Chi Zhang, Zilingfeng Ye, et al.*2024 · 624 citations*](https://md.research.elamur.ai/free/en/papers/sheng-2024-hybridflow-flexible-efficient-rlhf-framework/)
6. [**Orca: A Distributed Serving System for Transformer-Based Generative Models OSDI 2022**Gyeong-In Yu, Joo Seong Jeong, Geon-Woo Kim, et al.*2022 · 478 citations*](https://md.research.elamur.ai/free/en/papers/yu-2022-orca-distributed-serving-system-transformer/)
7. [**Tensor Comprehensions: Framework-Agnostic High-Performance Machine Learning Abstractions arXiv:1802.04730**Nicolas Vasilache, Oleksandr Zinenko, Theodoros Theodoridis, et al.*2018 · 323 citations*](https://md.research.elamur.ai/free/en/papers/vasilache-2018-tensor-comprehensions-framework-agnostic-high/)
8. [**Alpa: Automating Inter- and Intra-Operator Parallelism for Distributed Deep Learning OSDI 2022**Lianmin Zheng, Zhuohan Li, Hao Zhang, et al.*2022 · 279 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2022-alpa-automating-inter-intra-operator/)
9. [**Demystifying Parallel and Distributed Deep Learning: An In-Depth Concurrency Analysis ACM Computing Surveys 2019**Tal Ben-Nun, Torsten Hoefler*2018 · 275 citations*](https://md.research.elamur.ai/free/en/papers/nun-2018-demystifying-parallel-distributed-deep-learning/)
10. [**Learning to Optimize Tensor Programs arXiv:1805.08166**Tianqi Chen, Lianmin Zheng, Eddie Yan, et al.*2019 · 269 citations*](https://md.research.elamur.ai/free/en/papers/chen-2019-learning-optimize-tensor-programs/)
11. **[Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-towards-reasoning-era-survey-long/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Libo Qin, Jinhao Liu, et al.*2025 · 176 citations*
12. [**DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence arXiv:2606.19348**DeepSeek-AI, Anyi Xu, Bangcai Lin, et al.*2026 · 122 citations*](https://md.research.elamur.ai/free/en/papers/deepseek-ai-2026-deepseek-v4-highly-efficient/)
13. **[I-BERT: Integer-only BERT Quantization](https://md.research.elamur.ai/free/en/papers/kim-2021-i-bert-integer-only-bert/) [International Conference on Machine Learning (ICML)](https://md.research.elamur.ai/free/en/venues/international-conference-on-machine-learning/)**Sehoon Kim, Amir Gholami, Zhewei Yao, et al.*2021 · 122 citations*
14. [**Efficient Large Language Models: A Survey arXiv:2312.03863**Zhongwei Wan, Xin Wang, Che Liu, et al.*2023 · 110 citations*](https://md.research.elamur.ai/free/en/papers/wan-2023-efficient-large-language-models-survey/)
15. [**REINFORCE++: Stabilizing Critic-Free Policy Optimization with Global Advantage Normalization arXiv:2501.03262**Jian Hu, Jason Klein Liu, Haotian Xu, et al.*2025 · 104 citations*](https://md.research.elamur.ai/free/en/papers/hu-2025-reinforce-stabilizing-critic-free-policy/)
16. [**LLM Inference Unveiled: Survey and Roofline Model Insights arXiv 2024**Zhihang Yuan, Yuzhang Shang, Yang Zhou, et al.*2024 · 91 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2024-llm-inference-unveiled-survey-roofline/)
17. [**Liger Kernel: Efficient Triton Kernels for LLM Training arXiv:2410.10989**Pin-Lun Hsu, Yun Dai, Vignesh Kothapalli, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/hsu-2024-liger-kernel-efficient-triton-kernels/)
18. [**Zeus: Understanding and Optimizing GPU Energy Consumption of DNN Training arXiv:2208.06102**Jie You, Jae-Won Chung, Mosharaf Chowdhury*2022 · 82 citations*](https://md.research.elamur.ai/free/en/papers/you-2022-zeus-understanding-optimizing-gpu-energy/)
19. **[Insights into DeepSeek-V3: Scaling Challenges and Reflections on Hardware for AI Architectures](https://md.research.elamur.ai/free/en/papers/zhao-2025-insights-deepseek-v3-scaling/) [Proceedings - International Symposium on Computer Architecture/Proceedings](https://md.research.elamur.ai/free/en/venues/proceedings-international-symposium-on-computer-architecture-proceedings/)**Chenggang Zhao, Chengqi Deng, Chong Ruan, et al.*2025 · 74 citations*
20. [**TASO: Optimizing Deep Learning Computation with Automatic Generation of Graph Substitutions SOSP 2019**Zhihao Jia, Oded Padon, James Thomas, et al.*2019 · 72 citations*](https://md.research.elamur.ai/free/en/papers/jia-2019-taso-optimizing-deep-learning-computation/)
21. [**Seed1.5-VL Technical Report arXiv:2505.07062**Dong Guo, Faming Wu, Feida Zhu, et al.*2025 · 67 citations*](https://md.research.elamur.ai/free/en/papers/guo-2025-seed1-5-vl-technical/)
22. [**FLUX: Fast Software-based Communication Overlap On GPUs Through Kernel Fusion arXiv:2406.06858**Li-Wen Chang, Wenlei Bao, Qi Hou, et al.*2024 · 67 citations*](https://md.research.elamur.ai/free/en/papers/chang-2024-flux-fast-software-based-communication/)
23. [**MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention arXiv:2506.13585**MiniMax, Aili Chen, Aonian Li, et al.*2025 · 66 citations*](https://md.research.elamur.ai/free/en/papers/minimax-2025-minimax-m1-scaling-test/)
24. [**A Comprehensive Survey on Long Context Language Modeling arXiv:2503.17407**Jiaheng Liu, Dawei Zhu, Zhiqi Bai, et al.*2025 · 64 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-comprehensive-survey-long-context-language/)
25. [**Flex Attention: A Programming Model for Generating Optimized Attention Kernels arXiv:2412.05496**Juechu Dong, Boyuan Feng, Driss Guessous, et al.*2024 · 55 citations*](https://md.research.elamur.ai/free/en/papers/dong-2024-flex-attention-programming-model-generating/)
26. **[WebDancer: Towards Autonomous Information Seeking Agency](https://md.research.elamur.ai/free/en/papers/wu-2025-webdancer-towards-autonomous-information-seeking/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jialong Wu, Baixuan Li, Runnan Fang, et al.*2025 · 50 citations*
27. **[Fire-Flyer AI-HPC: A Cost-Effective Software-Hardware Co-Design for Deep Learning](https://md.research.elamur.ai/free/en/papers/an-2024-fire-flyer-ai-hpc/) [2012 International Conference for High Performance Computing, Networking, Storage and Analysis](https://md.research.elamur.ai/free/en/venues/2012-international-conference-for-high-performance-computing-networking-storage/)**Wei An, Xiao Bi, Guanting Chen, et al.*2024 · 34 citations*
28. [**Step-3 is Large yet Affordable: Model-system Co-design for Cost-effective Decoding arXiv:2507.19427**StepFun, Bin Wang, Bojun Wang, et al.*2025 · 26 citations*](https://md.research.elamur.ai/free/en/papers/stepfun-2025-step-3-large-yet/)
29. [**Seed-Coder: Let the Code Model Curate Data for Itself arXiv:2506.03524**ByteDance Seed, Yuyu Zhang, Jing Su, et al.*2025 · 25 citations*](https://md.research.elamur.ai/free/en/papers/bytedance-seed-2025-seed-coder-let-code/)
30. [**AceReason-Nemotron 1.1: Advancing Math and Code Reasoning through SFT and RL Synergy arXiv:2506.13284**Zihan Liu, Zhuolin Yang, Yang Chen, et al.*2025 · 21 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-acereason-nemotron-1-1-advancing/)
31. [**WideSearch: Benchmarking Agentic Broad Info-Seeking arXiv:2508.07999**Ryan Wong, Jiawei Wang, Junjie Zhao, et al.*2025 · 20 citations*](https://md.research.elamur.ai/free/en/papers/wong-2025-widesearch-benchmarking-agentic-broad-info/)
32. **[VerIF: Verification Engineering for Reinforcement Learning in Instruction Following](https://md.research.elamur.ai/free/en/papers/peng-2025-verif-verification-engineering-reinforcement-learning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Hao Peng, Yunjia Qi, Xiaozhi Wang, et al.*2025 · 18 citations*
33. [**Prolonged Reasoning Is Not All You Need: Certainty-Based Adaptive Routing for Efficient LLM/MLLM Reasoning arXiv:2505.15154**Jinghui Lu, Haiyang Yu, Siliang Xu, et al.*2025 · 11 citations*](https://md.research.elamur.ai/free/en/papers/lu-2025-prolonged-reasoning-all-need-certainty/)
34. **[What Makes a Good Reasoning Chain? Uncovering Structural Patterns in Long Chain-of-Thought Reasoning](https://md.research.elamur.ai/free/en/papers/jiang-2025-what-makes-good-reasoning-chain/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Gangwei Jiang, Yahui Liu, Zhaoyi Li, et al.*2025 · 11 citations*
35. [**Yi-Lightning Technical Report arXiv:2412.01253**Alan Wake, Bei Chen, C.X. Lv, et al.*2024 · 11 citations*](https://md.research.elamur.ai/free/en/papers/wake-2024-yi-lightning-technical-report/)
36. **[ReviewRL: Towards Automated Scientific Review with RL](https://md.research.elamur.ai/free/en/papers/zeng-2025-reviewrl-automated-scientific-review-rl/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Sihang Zeng, Kai Tian, Kaiyan Zhang, et al.*2025 · 9 citations*
37. **[EquiBench: Benchmarking Large Language Models' Reasoning about Program Semantics via Equivalence Checking](https://md.research.elamur.ai/free/en/papers/wei-2025-equibench-benchmarking-large-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Anjiang Wei, Jiannan Cao, Ran Li, et al.*2025 · 8 citations*
38. [**PAG: Multi-Turn Reinforced LLM Self-Correction with Policy as Generative Verifier arXiv:2506.10406**Yuhua Jiang, Yuwen Xiong, Yufeng Yuan, et al.*2025 · 8 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2025-pag-multi-turn-reinforced-llm/)
39. **[NOVER: Incentive Training for Language Models via Verifier-Free Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/liu-2025-nover-incentive-training-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wei Liu, Siya Qi, Xinyu Wang, et al.*2025 · 7 citations*
40. [**Pangu Ultra: Pushing the Limits of Dense Large Language Models on Ascend NPUs arXiv:2504.07866**Yichun Yin, Wenyong Huang, Kaikai Song, et al.*2025 · 6 citations*](https://md.research.elamur.ai/free/en/papers/yin-2025-pangu-ultra-pushing-limits/)
41. [**rStar2-Agent: Agentic Reasoning Technical Report arXiv:2508.20722**Ning Shang, Yifei Liu, Yi Zhu, et al.*2025 · 6 citations*](https://md.research.elamur.ai/free/en/papers/shang-2025-rstar2-agent-agentic-reasoning/)
42. **[DeepPlanning: Benchmarking Long-Horizon Agentic Planning with Verifiable Constraints](https://md.research.elamur.ai/free/en/papers/zhang-2026-deepplanning-benchmarking-long-horizon-agentic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yinger Zhang, Shutong Jiang, Renhao Li, et al.*2026 · 5 citations*
43. **[Mathematical Proof as a Litmus Test: Revealing Failure Modes of Advanced Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/guo-2026-mathematical-proof-as-litmus-test/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dadi Guo, Jiayu Liu, Zhiyuan Fan, et al.*2026 · 5 citations*
44. **[Teach Small Models to Reason by Curriculum Distillation](https://md.research.elamur.ai/free/en/papers/jiang-2025-teach-small-models-reason-curriculum/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wangyi Jiang, Yaojie Lu, Hongyu Lin, et al.*2025 · 5 citations*
45. [**Kimi-Dev: Agentless Training as Skill Prior for SWE-Agents arXiv:2509.23045**Zonghan Yang, Shengjie Wang, Kelin Fu, et al.*2025 · 4 citations*](https://md.research.elamur.ai/free/en/papers/yang-2025-kimi-dev-agentless-training/)
46. **[Instructions are all you need: Self-supervised Reinforcement Learning for Instruction Following](https://md.research.elamur.ai/free/en/papers/ren-2026-instructions-are-all-you-need/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qingyu Ren, Qianyu He, Powei Chang, et al.*2026 · 3 citations*
47. **[MathCanvas: Intrinsic Visual Chain-of-Thought for Multimodal Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/shi-2026-mathcanvas-intrinsic-visual-chain-thought/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weikang Shi, Aldrich Yu, Rongyao Fang, et al.*2026 · 3 citations*
48. **[Deep Kernel Fusion for Transformers](https://md.research.elamur.ai/free/en/papers/zhang-2026-deep-kernel-fusion-transformers/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zixi Zhang, Zhiwen Mo, Yiren Zhao, et al.*2026 · 1 citation*
49. **[Entropy Ratio Clipping as a Soft Global Constraint for Stable Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/su-2026-entropy-ratio-clipping-as-soft/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhenpeng Su, Leiyu Pan, Minxuan Lv, et al.*2026 · 1 citation*
50. **[ARM2: Adaptive Reasoning Model with Vision Understanding and Executable Code](https://md.research.elamur.ai/free/en/papers/xie-2026-arm2-adaptive-reasoning-model-vision/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jian Xie, Zhendong Chu, Aoxiao Zhong, et al.*2026*
51. **[Beyond Reasoning Gains: Mitigating General-Capability Forgetting in Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/phan-2026-beyond-reasoning-gains-mitigating-general/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hoang Phan, Xianjun Yang, Yuanshun Yao, et al.*2026*
52. **[JanusMM: A Benchmark for Self-Deprecation Understanding in Real-World Multimodal Conversations](https://md.research.elamur.ai/free/en/papers/xu-2026-janusmm-benchmark-self-deprecation-understanding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinyi Xu, Bingguang Hao, Yongyi Xiong, et al.*2026*
53. **[PARIF: Pushing the Pareto Frontier of Instruction Following and Reasoning with Curriculum Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/mu-2026-parif-pushing-pareto-frontier-instruction/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rongchuan Mu, Zexin Wang, Qianyu Wang, et al.*2026*
54. **[PRIME: A Process-Outcome Alignment Benchmark for Verifiable Reasoning in Mathematics and Engineering](https://md.research.elamur.ai/free/en/papers/wang-2026-prime-process-outcome-alignment-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiangfeng Wang, Hangyu Guo, Yanlin Lai, et al.*2026*
55. **[ReflectRM: Boosting Generative Reward Models via Self-Reflection within a Unified Judgment Framework](https://md.research.elamur.ai/free/en/papers/qin-2026-reflectrm-boosting-generative-reward-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kai Qin, Liangxin Liu, Yu Liang, et al.*2026*
56. **[RepoDistill: Distilling Repository Knowledge through Compression-Aware Budget Allocation and Policy Optimization](https://md.research.elamur.ai/free/en/papers/yin-2026-repodistill-distilling-repository-knowledge-through/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xin Yin, Zixiang Ding, Yiang Zhang, et al.*2026*
57. **[ROMA: Real-time Omni-Multimodal Assistant with Interactive Streaming Understanding](https://md.research.elamur.ai/free/en/papers/xueyun-2026-roma-real-time-omni-multimodal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tian Xueyun, Wei Li, Bingbing Xu, et al.*2026*
58. **[V-RoLoRA: RLVR-Driven MoE Routing for Steerable Pluralistic Alignment](https://md.research.elamur.ai/free/en/papers/wang-2026-v-rolora-rlvr-driven-moe/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jing Wang, Yaomin Wu, Yinglin Wang, et al.*2026*
59. **[Survey on Key Technologies for Large Language Model Pre-training Systems (大语言模型预训练系统关键技术综述)](https://md.research.elamur.ai/free/en/papers/gao-2025-key-technologies-large/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Yanjie Gao (高彦杰), Yueguo Chen (陈跃国)*2025*

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

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