---
title: "Who cites Junjie Li — 128 papers of our library"
description: "128 papers of the Elamur Research library cite the works of Junjie Li, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/junjie-li/cited-by/"
---
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# Who cites Junjie Li

128 citations of their works from 128 papers of our library (of the 149,439 whose bibliographies we read) · 38 with a page here, the most cited first · [← Junjie Li](https://md.research.elamur.ai/free/en/authors/junjie-li/)

1. **[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*
2. [**LongWriter: Unleashing 10,000+ Word Generation from Long Context LLMs arXiv:2408.07055**Yushi Bai, Jiajie Zhang, Xin Lv, et al.*2024 · 66 citations*](https://md.research.elamur.ai/free/en/papers/bai-2024-longwriter-unleashing-10-000/)
3. [**Self-play with Execution Feedback: Improving Instruction-following Capabilities of Large Language Models arXiv:2406.13542**Guanting Dong, Keming Lu, Chengpeng Li, et al.*2024 · 54 citations*](https://md.research.elamur.ai/free/en/papers/dong-2024-self-play-execution-feedback-improving/)
4. **[Checklists Are Better Than Reward Models For Aligning Language Models](https://md.research.elamur.ai/free/en/papers/viswanathan-2025-checklists-better-than-reward-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Vijay Viswanathan, Yanchao Sun, Shuang Ma, et al.*2025 · 37 citations*
5. **[CFBench: A Comprehensive Constraints-Following Benchmark for LLMs](https://md.research.elamur.ai/free/en/papers/zhang-2025-cfbench-comprehensive-constraints-following-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tao Zhang, ChengLIn Zhu, Yanjun Shen, et al.*2025 · 30 citations*
6. [**TICKing All the Boxes: Generated Checklists Improve LLM Evaluation and Generation arXiv:2410.03608**Jonathan Cook, Tim Rocktaschel, Jakob Foerster, et al.*2024 · 29 citations*](https://md.research.elamur.ai/free/en/papers/cook-2024-ticking-all-boxes-generated-checklists/)
7. **[Sub-Character Tokenization for Chinese Pretrained Language Models](https://md.research.elamur.ai/free/en/papers/si-2023-sub-character-tokenization-chinese-pretrained/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Chenglei Si, Zhengyan Zhang, Yingfa Chen, et al.*2023 · 29 citations*
8. **[OpenRubrics: Towards Scalable Synthetic Rubric Generation for Reward Modeling and LLM Alignment](https://md.research.elamur.ai/free/en/papers/liu-2026-openrubrics-scalable-synthetic-rubric-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianci Liu, Ran Xu, Tony Yu, et al.*2026 · 25 citations*
9. **[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*
10. **[IOPO: Empowering LLMs with Complex Instruction Following via Input-Output Preference Optimization](https://md.research.elamur.ai/free/en/papers/zhang-2025-iopo-empowering-llms-complex-instruction/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinghua Zhang, Haiyang Yu, Cheng Fu, et al.*2025 · 14 citations*
11. **[Pre-training Distillation for Large Language Models: A Design Space Exploration](https://md.research.elamur.ai/free/en/papers/peng-2025-pre-training-distillation-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Peng, Xin Lv, Yushi Bai, et al.*2025 · 14 citations*
12. [**Rethinking Rubric Generation for Improving LLM Judge and Reward Modeling for Open-ended Tasks arXiv:2602.05125**William F. Shen, Xinchi Qiu, Chenxi Whitehouse, et al.*2026 · 9 citations*](https://md.research.elamur.ai/free/en/papers/shen-2026-rethinking-rubric-generation-improving-llm/)
13. [**HunyuanOCR Technical Report arXiv:2511.19575**Hunyuan Vision Team, Pengyuan Lyu, Xingyu Wan, et al.*2025 · 9 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-vision-hunyuanocr-technical-report/)
14. **[Thinking beyond the anthropomorphic paradigm benefits LLM research](https://md.research.elamur.ai/free/en/papers/ibrahim-2026-thinking-beyond-anthropomorphic-paradigm-benefits/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lujain Ibrahim, Myra Cheng*2026 · 8 citations*
15. **[UltraIF: Advancing Instruction Following from the Wild](https://md.research.elamur.ai/free/en/papers/an-2025-ultraif-advancing-instruction-following-wild/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kaikai An, Li Sheng, Ganqu Cui, et al.*2025 · 7 citations*
16. **[EIFBENCH: Extremely Complex Instruction Following Benchmark for Large Language Models](https://md.research.elamur.ai/free/en/papers/zou-2025-eifbench-extremely-complex-instruction-following/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tao Zou, Xinghua Zhang, Haiyang Yu, et al.*2025 · 5 citations*
17. [**Baichuan Alignment Technical Report arXiv:2410.14940**Mingan Lin, Fan Yang, Yanjun Shen, et al.*2024 · 5 citations*](https://md.research.elamur.ai/free/en/papers/lin-2024-baichuan-alignment-technical-report/)
18. **[Beyond Majority Voting: Towards Fine-grained and More Reliable Reward Signal for Test-Time Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/wang-2026-beyond-majority-voting-fine-grained/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weiqin Wang, Yile Wang, Kehao Chen, et al.*2026 · 4 citations*
19. **[MulDimIF: A Multi-Dimensional Constraint Framework for Evaluating and Improving Instruction Following in Large Language Models](https://md.research.elamur.ai/free/en/papers/ye-2026-muldimif-multi-dimensional-constraint-framework/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Junjie Ye, Caishuang Huang, Zhuohan Chen, et al.*2026 · 4 citations*
20. **[MuSC: Improving Complex Instruction Following with Multi-granularity Self-Contrastive Training](https://md.research.elamur.ai/free/en/papers/huang-2025-musc-improving-complex-instruction-following/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hui Huang, Jiaheng Liu, Yancheng He, et al.*2025 · 4 citations*
21. **[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*
22. **[No More Stale Feedback: Co-Evolving Critics for Open-World Agent Learning](https://md.research.elamur.ai/free/en/papers/li-2026-no-more-stale-feedback-co/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhicong Li, Lingjie Jiang, Yulan Hu, et al.*2026 · 3 citations*
23. **[Beyond Outcome Verification: Verifiable Process Reward Models for Structured Reasoning](https://md.research.elamur.ai/free/en/papers/pronesti-2026-beyond-outcome-verification-verifiable-process/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Massimiliano Pronesti, Anya Belz, Yufang Hou*2026 · 2 citations*
24. **[A Comprehensive Evaluation of Chain-of-Thought Faithfulness in Persian Classification Tasks](https://md.research.elamur.ai/free/en/papers/yazdani-2026-comprehensive-evaluation-chain-thought-faithfulness/) [Workshop on Language Models for Low-Resource Languages](https://md.research.elamur.ai/free/en/venues/loreslm/)**Shakib Yazdani, Cristina España-Bonet, Eleftherios Avramidis, et al.*2026 · 1 citation*
25. **[CSRP: Chain-of-Thought Reasoning for Chinese Text Correction via Reinforcement Learning with Efficiency-Aware Rewards](https://md.research.elamur.ai/free/en/papers/tian-2026-csrp-chain-thought-reasoning-chinese/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wei Tian, Yuhao Zhou, Man Lan*2026 · 1 citation*
26. **[IF-CRITIC: Towards a Fine-Grained LLM Critic for Instruction-Following Evaluation](https://md.research.elamur.ai/free/en/papers/wen-2026-if-critic-fine-grained-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bosi Wen, Yilin Niu, Cunxiang Wang, et al.*2026 · 1 citation*
27. **[AT\texttwosuperiorPO: Agentic Turn-based Policy Optimization via Tree Search](https://md.research.elamur.ai/free/en/papers/zong-2026-texttwosuperiorpo-agentic-turn-based-policy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zefang Zong, Dingwei Chen, Yang Li, et al.*2026*
28. **[DSMentor: Curriculum-Guided Inference with Online Memory for Data-Science LLM Agents](https://md.research.elamur.ai/free/en/papers/wang-2026-dsmentor-curriculum-guided-inference-online/) [Workshop on Structured Understanding, Retrieval, and Generation in the LLM Era](https://md.research.elamur.ai/free/en/venues/surgellm/)**He Wang, Alexander Hanbo Li, Yiqun Hu, et al.*2026*
29. **[Evo-PI: Aligning Medical Reasoning via Evolving Principle-Guided Supervision](https://md.research.elamur.ai/free/en/papers/zheng-2026-evo-pi-aligning-medical-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xianda Zheng, Huan Gao, Meng-Fen Chiang, et al.*2026*
30. **[ImpRIF: Stronger Implicit Reasoning Leads to Better Complex Instruction Following](https://md.research.elamur.ai/free/en/papers/yang-2026-imprif-stronger-implicit-reasoning-leads/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuancheng Yang, Lin Yang, Xu Wang, et al.*2026*
31. **[MDP-GRPO: Stabilized Group Relative Policy Optimization for Multi-Constraint Instruction Following](https://md.research.elamur.ai/free/en/papers/zarchi-2026-mdp-grpo-stabilized-group-relative/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mohammad Mahdi Salmani-Zarchi, Zahra Rahimi, Heshaam Faili, et al.*2026*
32. **[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*
33. **[Reward Modeling for Scientific Writing Evaluation](https://md.research.elamur.ai/free/en/papers/sahinuc-2026-reward-modeling-scientific-writing-evaluation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Furkan Şahinuç, Subhabrata Dutta, Iryna Gurevych*2026*
34. **[ScaleBox: Enabling High-Fidelity and Scalable Code Verification for Large Language Models](https://md.research.elamur.ai/free/en/papers/zheng-2026-scalebox-enabling-high-fidelity-scalable/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiasheng Zheng, Xin Zheng, Boxi Cao, et al.*2026*
35. **[Sem-DPO: Mitigating Semantic Inconsistency in Preference Optimization for Prompt Engineering](https://md.research.elamur.ai/free/en/papers/mohamed-2026-sem-dpo-mitigating-semantic-inconsistency/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Anas Mohamed, Azal Ahmad Khan, Xinran Wang, et al.*2026*
36. **[Tailored Primitive Initialization is the Secret Key to Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/yao-2026-tailored-primitive-initialization-is-secret/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yihang Yao, Guangtao Zeng, Raina Wu, et al.*2026*
37. **[Tandem Training for Language Models](https://md.research.elamur.ai/free/en/papers/west-2026-tandem-training-language-models/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Robert West, Ashton Anderson, Ece Kamar, et al.*2026*
38. **[The Inner Monologue of Language Models: When Reasoning Traces Reveal More Than They Hide](https://md.research.elamur.ai/free/en/papers/singla-2026-inner-monologue-language-models-when/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Pratham Singla, Shivank Garg, Ayush Singh, et al.*2026*

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

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