--- title: "Who cites Bingxuan Li — 107 papers of our library" description: "107 papers of the Elamur Research library cite the works of Bingxuan Li, found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/authors/bingxuan-li/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/bingxuan-li/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Bingxuan Li](https://md.research.elamur.ai/free/en/authors/bingxuan-li/) / cited by # Who cites Bingxuan Li 107 citations of their works from 107 papers of our library (of the 149,439 whose bibliographies we read) · 22 with a page here, the most cited first · [← Bingxuan Li](https://md.research.elamur.ai/free/en/authors/bingxuan-li/) 1. [**Retrieval-Augmented Generation for AI-Generated Content: A Survey arXiv:2402.19473**Penghao Zhao, Hailin Zhang, Qinhan Yu, et al.*2024 · 301 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2024-retrieval-augmented-generation-ai-generated/) 2. [**TrustLLM: Trustworthiness in Large Language Models arXiv:2401.05561**Yue Huang, Lichao Sun, Haoran Wang, et al.*2024 · 237 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-trustllm-trustworthiness-large-language-models/) 3. [**LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods arXiv:2412.05579**Haitao Li, Qian Dong, Junjie Chen, et al.*2024 · 195 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llms-judges-comprehensive-survey-llm/) 4. [**LawBench: Benchmarking Legal Knowledge of Large Language Models arXiv:2309.16289**Zhiwei Fei, Xiaoyu Shen, Dawei Zhu, et al.*2023 · 186 citations*](https://md.research.elamur.ai/free/en/papers/fei-2023-lawbench-benchmarking-legal-knowledge-large/) 5. **[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* 6. **[A Comprehensive Survey of Small Language Models in the Era of Large Language Models: Techniques, Enhancements, Applications, Collaboration with LLMs, and Trustworthiness](https://md.research.elamur.ai/free/en/papers/wang-2024-comprehensive-survey-small-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Fali Wang, Zhiwei Zhang, Xianren Zhang, et al.*2024 · 159 citations* 7. [**A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well? arXiv:2503.24235**Qiyuan Zhang, Fuyuan Lyu, Zexu Sun, et al.*2025 · 79 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2025-survey-test-time-scaling-large/) 8. [**Large Language Model Agent: A Survey on Methodology, Applications and Challenges arXiv:2503.21460**Junyu Luo, Weizhi Zhang, Ye Yuan, et al.*2025 · 62 citations*](https://md.research.elamur.ai/free/en/papers/luo-2025-large-language-model-agent-survey/) 9. **[LAiW: A Chinese Legal Large Language Models Benchmark](https://md.research.elamur.ai/free/en/papers/dai-2025-laiw-chinese-legal-large-language/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Yongfu Dai, Duanyu Feng, Jimin Huang, et al.*2025 · 35 citations* 10. **[What is the Role of Small Models in the LLM Era: A Survey](https://md.research.elamur.ai/free/en/papers/chen-2024-role-small-models-llm-era/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Lihu Chen, Gael Varoquaux*2024 · 23 citations* 11. **[RCBSF: A Multi-Agent Framework for Automated Contract Revision via Stackelberg Game](https://md.research.elamur.ai/free/en/papers/xu-2026-rcbsf-multi-agent-framework-automated/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shijia Xu, Yu Wang, Xiaolong Jia, et al.*2026 · 11 citations* 12. [**PanGu-π: Enhancing Language Model Architectures via Nonlinearity Compensation arXiv:2312.17276**Yunhe Wang, Hanting Chen, Yehui Tang, et al.*2023 · 10 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-pangu-pi-enhancing-language/) 13. [**InternLM-Law: An Open Source Chinese Legal Large Language Model arXiv:2406.14887**Zhiwei Fei, Songyang Zhang, Xiaoyu Shen, et al.*2024 · 9 citations*](https://md.research.elamur.ai/free/en/papers/fei-2024-internlm-law-open-source/) 14. **[Curriculum Learning based Hierarchical Scoring and Analysis Framework for Question Answering Task Evaluation](https://md.research.elamur.ai/free/en/papers/wu-2026-curriculum-learning-based-hierarchical-scoring/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qiong Wu, Tan Yue, Jianxin Liang, et al.*2026* 15. **[Deep-Reporter: Deep Research for Grounded Multimodal Long-Form Generation](https://md.research.elamur.ai/free/en/papers/ye-2026-deep-reporter-deep-research-grounded/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fangda Ye, Kuicai Dong, Xie Zhifei, et al.*2026* 16. **[Feedback-Aware Prompt Optimization Framework for Generating Job Postings](https://md.research.elamur.ai/free/en/papers/maharjan-2026-feedback-aware-prompt-optimization-framework/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Suraj Maharjan, Ainur Yessenalina, Srinivasan H. Sengamedu*2026* 17. **[Knowledge-to-Verification: Exploring RLVR for LLMs in Knowledge-Intensive Domains](https://md.research.elamur.ai/free/en/papers/yuan-2026-knowledge-verification-exploring-rlvr-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhonghang Yuan, Zhefan Wang, Fang Hu, et al.*2026* 18. [**Qwen-AgentWorld: Language World Models for General Agents arXiv:2606.24597**Yuxin Zuo, Zikai Xiao, Li Sheng, et al.*2026*](https://md.research.elamur.ai/free/en/papers/zuo-2026-qwen-agentworld-language-world/) 19. **[RADO: Reasoning Audit-Driven Optimization for Rigorous Reasoning in High-Stakes Domains](https://md.research.elamur.ai/free/en/papers/tan-2026-rado-reasoning-audit-driven-optimization/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhijie Tan, Xu Chu, Guanyu Wang, et al.*2026* 20. **[RoadMapper: A Multi-Agent System for Roadmap Generation of Solving Complex Research Problems](https://md.research.elamur.ai/free/en/papers/liu-2026-roadmapper-multi-agent-system-roadmap/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiacheng Liu, Zichen Tang, Zhongjun Yang, et al.*2026* 21. **[Test-Time Scaling in Multimodal Foundation Models: A Comprehensive Survey of Generation and Reasoning](https://md.research.elamur.ai/free/en/papers/wan-2026-test-time-scaling-multimodal-foundation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Cong Wan, Ying He, Zhongzhan Huang, et al.*2026* 22. **[ToolCPT: Improving Tool Utilization in LLM Agents via Continuous Pre-training](https://md.research.elamur.ai/free/en/papers/yang-2026-toolcpt-improving-tool-utilization-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yifan Yang, Jinghui Lu, Evadeng, et al.*2026* 85 more citing papers of our library have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/authors/bingxuan-li/) — Bingxuan Li