---
title: "Who cites Fenglu Hong — 124 papers of our library"
description: "124 papers of the Elamur Research library cite the works of Fenglu Hong, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/fenglu-hong/cited-by/"
---
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# Who cites Fenglu Hong

127 citations of their works from 124 papers of our library (of the 149,439 whose bibliographies we read) · 46 with a page here, the most cited first · [← Fenglu Hong](https://md.research.elamur.ai/free/en/authors/fenglu-hong/)

1. **[A Survey of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,875 citations*
2. **[A Comprehensive Overview of Large Language Models](https://md.research.elamur.ai/free/en/papers/naveed-2023-comprehensive-overview-large-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Humza Naveed, Asad Ullah Khan, Shi Qiu, et al.*2023 · 1,287 citations*
3. [**ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs arXiv:2307.16789**Yujia Qin, Shihao Liang, Yining Ye, et al.*2023 · 589 citations*](https://md.research.elamur.ai/free/en/papers/qin-2023-toolllm-facilitating-large-language-models/)
4. **[API-Bank: A Comprehensive Benchmark for Tool-Augmented LLMs](https://md.research.elamur.ai/free/en/papers/li-2023-api-bank-comprehensive-benchmark-tool/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Minghao Li, Yingxiu Zhao, Bowen Yu, et al.*2023 · 286 citations*
5. [**GAIA: a benchmark for General AI Assistants arXiv:2311.12983**Gregoire Mialon, Clementine Fourrier, Craig Swift, et al.*2023 · 232 citations*](https://md.research.elamur.ai/free/en/papers/mialon-2023-gaia-benchmark-general-ai-assistants/)
6. [**Prompt Injection attack against LLM-integrated Applications arXiv:2306.05499**Yi Liu; Gelei Deng; Yuekang Li; Kailong Wang; Zihao Wang; Xiaofeng Wang; Tianwei Zhang; Yepang Liu; Haoyu Wang; Yan Zheng; Leo Yu Zhang;, Yang Liu*2023 · 208 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-prompt-injection-attack-against-llm/)
7. **[Tool Learning with Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/qu-2024-tool-learning-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Changle Qu, Sunhao Dai, Xiaochi Wei, et al.*2024 · 195 citations*
8. [**Evaluating Large Language Models: A Comprehensive Survey arXiv:2310.19736**Zishan Guo, Renren Jin, Chuang Liu, et al.*2023 · 182 citations*](https://md.research.elamur.ai/free/en/papers/guo-2023-evaluating-large-language-models-comprehensive/)
9. **[ToolQA: A Dataset for LLM Question Answering with External Tools](https://md.research.elamur.ai/free/en/papers/zhuang-2023-toolqa-dataset-llm-question-answering/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yuchen Zhuang, Yue Yu, Kuan Wang, et al.*2023 · 182 citations*
10. [**ToolAlpaca: Generalized Tool Learning for Language Models with 3000 Simulated Cases arXiv:2306.05301**Qiaoyu Tang, Ziliang Deng, Hongyu Lin, et al.*2023 · 180 citations*](https://md.research.elamur.ai/free/en/papers/tang-2023-toolalpaca-generalized-tool-learning-language/)
11. [**Executable Code Actions Elicit Better LLM Agents arXiv:2402.01030**Xingyao Wang, Yangyi Chen, Lifan Yuan, et al.*2024 · 165 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-executable-code-actions-elicit-better/)
12. [**τ-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains arXiv:2406.12045**Shunyu Yao, Noah Shinn, Pedram Razavi, et al.*2024 · 137 citations*](https://md.research.elamur.ai/free/en/papers/yao-2024-tau-bench-benchmark-tool/)
13. [**TravelPlanner: A Benchmark for Real-World Planning with Language Agents arXiv:2402.01622**Jian Xie, Kai Zhang, Jiangjie Chen, et al.*2024 · 125 citations*](https://md.research.elamur.ai/free/en/papers/xie-2024-travelplanner-benchmark-real-world-planning/)
14. [**From Persona to Personalization: A Survey on Role-Playing Language Agents arXiv:2404.18231**Jiangjie Chen, Xintao Wang, Rui Xu, et al.*2024 · 115 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-persona-personalization-survey-role-playing/)
15. **[AgentBoard: An Analytical Evaluation Board of Multi-turn LLM Agents](https://md.research.elamur.ai/free/en/papers/ma-2024-agentboard-analytical-evaluation-board-multi/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Chang Ma, Junlei Zhang, Zhihao Zhu, et al.*2024 · 90 citations*
16. [**Foundational Challenges in Assuring Alignment and Safety of Large Language Models arXiv:2404.09932**Usman Anwar, Abulhair Saparov, Javier Rando, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/anwar-2024-foundational-challenges-assuring-alignment-safety/)
17. [**AndroidWorld: A Dynamic Benchmarking Environment for Autonomous Agents arXiv:2405.14573**Christopher Rawles, Sarah Clinckemaillie, Yifan Chang, et al.*2024 · 82 citations*](https://md.research.elamur.ai/free/en/papers/rawles-2024-androidworld-dynamic-benchmarking-environment-autonomous/)
18. [**MetaTool Benchmark for Large Language Models: Deciding Whether to Use Tools and Which to Use arXiv:2310.03128**Yue Huang, Jiawen Shi, Yuan Li, et al.*2023 · 81 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-metatool-benchmark-large-language-models/)
19. **[AppWorld: A Controllable World of Apps and People for Benchmarking Interactive Coding Agents](https://md.research.elamur.ai/free/en/papers/trivedi-2024-appworld-controllable-world-apps-people/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Harsh Trivedi, Tushar Khot, Mareike Hartmann, et al.*2024 · 80 citations*
20. **[PlanGenLLMs: A Modern Survey of LLM Planning Capabilities](https://md.research.elamur.ai/free/en/papers/wei-2025-plangenllms-modern-survey-llm-planning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hui Wei, Zihao Zhang, Shenghua He, et al.*2025 · 55 citations*
21. **[SciAgent: Tool-augmented Language Models for Scientific Reasoning](https://md.research.elamur.ai/free/en/papers/ma-2024-sciagent-tool-augmented-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yubo Ma, Zhibin Gou, Junheng Hao, et al.*2024 · 55 citations*
22. [**StableToolBench: Towards Stable Large-Scale Benchmarking on Tool Learning of Large Language Models arXiv:2403.07714**Zhicheng Guo, Sijie Cheng, Hao Wang, et al.*2024 · 55 citations*](https://md.research.elamur.ai/free/en/papers/guo-2024-stabletoolbench-towards-stable-large-scale/)
23. **[BioCoder: A Benchmark for Bioinformatics Code Generation with Large Language Models](https://md.research.elamur.ai/free/en/papers/tang-2023-biocoder-benchmark-bioinformatics-code-generation/) [Bioinformatics](https://md.research.elamur.ai/free/en/venues/bioinformatics/)**Xiangru Tang, Bill Qian, Rick Gao, et al.*2023 · 38 citations*
24. [**A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence arXiv:2507.21046**Huan-ang Gao, Jiayi Geng, Wenyue Hua, et al.*2025 · 36 citations*](https://md.research.elamur.ai/free/en/papers/gao-2025-survey-self-evolving-agents-where/)
25. **[ToolEyes: Fine-Grained Evaluation for Tool Learning Capabilities of Large Language Models in Real-world Scenarios](https://md.research.elamur.ai/free/en/papers/ye-2025-tooleyes-fine-grained-evaluation-tool/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Junjie Ye, Guanyu Li, SongYang Gao, et al.*2025 · 35 citations*
26. **[A Survey on Evaluation of LLM-based Agents](https://md.research.elamur.ai/free/en/papers/yehudai-2026-survey-evaluation-llm-based-agents/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Asaf Yehudai, Lilach Eden, Alan Li, et al.*2026 · 21 citations*
27. **[NESTFUL: A Benchmark for Evaluating LLMs on Nested Sequences of API Calls](https://md.research.elamur.ai/free/en/papers/basu-2025-nestful-benchmark-evaluating-llms-nested/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kinjal Basu, Ibrahim Abdelaziz, Kiran Kate, et al.*2025 · 16 citations*
28. **[Efficient Tool Use with Chain-of-Abstraction Reasoning](https://md.research.elamur.ai/free/en/papers/gao-2025-efficient-tool-use-chain-abstraction/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Silin Gao, Jane Dwivedi-Yu, Ping Yu, et al.*2025 · 13 citations*
29. **[CRITICTOOL: Evaluating Self-Critique Capabilities of Large Language Models in Tool-Calling Error Scenarios](https://md.research.elamur.ai/free/en/papers/huang-2025-critictool-evaluating-self-critique-capabilities/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shiting Huang, Zhen Fang, Zehui Chen, et al.*2025 · 12 citations*
30. **[When2Call: When (not) to Call Tools](https://md.research.elamur.ai/free/en/papers/ross-2025-when2call-when-not-call-tools/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Hayley Ross, Ameya Sunil Mahabaleshwarkar, Yoshi Suhara*2025 · 11 citations*
31. [**AI for Auto-Research: Roadmap & User Guide arXiv:2605.18661**Lingdong Kong, Xian Sun, Wei Chow, et al.*2026 · 5 citations*](https://md.research.elamur.ai/free/en/papers/kong-2026-ai-auto-research-roadmap-user/)
32. **[ToolScope: Enhancing LLM Agent Tool Use through Tool Merging and Context-Aware Filtering](https://md.research.elamur.ai/free/en/papers/liu-2026-toolscope-enhancing-llm-agent-tool/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Marianne Menglin Liu, Daniel Garcia, Fjona Parllaku, et al.*2026 · 4 citations*
33. **[Prompt-R1: Collaborative Automatic Prompting Framework via End-to-end Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/liu-2026-prompt-r1-collaborative-automatic-prompting/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenjin Liu, Haoran Luo, Xueyuan Lin, et al.*2026 · 3 citations*
34. **[Mistake Notebook Learning: Batch-Clustered Failures for Training-Free Agent Adaptation](https://md.research.elamur.ai/free/en/papers/su-2026-mistake-notebook-learning-batch-clustered/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xuanbo Su, Yingfang Zhang, Hao Luo, et al.*2026 · 2 citations*
35. **[On Safety Risks in Experience-Driven Self-Evolving Agents](https://md.research.elamur.ai/free/en/papers/zhao-2026-safety-risks-experience-driven-self/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Weixiang Zhao, Yichen Zhang, Yingshuo Wang, et al.*2026 · 1 citation*
36. **[UIT-AMMC at SemEval-2026 Task 13: Exploiting Structural Formatting Signatures for Robust AI-Generated Code Detection](https://md.research.elamur.ai/free/en/papers/pham-2026-uit-ammc-semeval-2026-task/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Cuong Pham, Minh Nguyen, Minh Le, et al.*2026 · 1 citation*
37. **[What Makes an LLM a Good Optimizer? A Trajectory Analysis of LLM-Guided Evolutionary Search](https://md.research.elamur.ai/free/en/papers/zhang-2026-what-makes-llm-good-optimizer/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xinhao Zhang, Xi Chen, François Portet, et al.*2026 · 1 citation*
38. [**Workflow Closure Is Not Scientific Closure in Auto-Research Systems arXiv:2605.26200**Shuai Wang, Xinyuan Tian, Pangpang Liu, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/wang-2026-workflow-closure-scientific-closure/)
39. **[ARC: Active and Reflection-driven Context Management for Long-Horizon Information Seeking Agents](https://md.research.elamur.ai/free/en/papers/yao-2026-arc-active-reflection-driven-context/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yilun Yao, Shan Huang, Elsie Dai, et al.*2026*
40. **[Importance of Prompt Optimisation for Error Detection in Medical Notes Using Language Models](https://md.research.elamur.ai/free/en/papers/myles-2026-importance-prompt-optimisation-error-detection/) [Workshop on Linguistic Analysis for Health](https://md.research.elamur.ai/free/en/venues/healing/)**Craig Myles, Patrick Schrempf, David Harris-Birtill*2026*
41. **[LEDGER: Scaling Agentic Document Editing with Dependency-aware Graph Retrieval](https://md.research.elamur.ai/free/en/papers/wang-2026-ledger-scaling-agentic-document-editing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hang Wang, Utkarsh Garg, Reza Davari, et al.*2026*
42. **[NaturalGAIA: A Verifiable Benchmark and Hierarchical Framework for Long-Horizon GUI Tasks](https://md.research.elamur.ai/free/en/papers/zheng-2026-naturalgaia-verifiable-benchmark-hierarchical-framework/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zihan Zheng, Tianle Cui, Taoran Wang, et al.*2026*
43. **[PyraMathBench: Evaluating and Improving Mathematical Capability in Large Language Models](https://md.research.elamur.ai/free/en/papers/ouyang-2026-pyramathbench-evaluating-improving-mathematical-capability/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zetian Ouyang, Linlin Wang, Gerard de Melo, et al.*2026*
44. **[Telling Speculative Stories to Help Humans Imagine the Harms of Healthcare AI](https://md.research.elamur.ai/free/en/papers/zhao-2026-telling-speculative-stories-help-humans/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xingmeng Zhao, Tongnian Wang, Dan Schumacher, et al.*2026*
45. **[When Users Are Happy but Agents Are Wrong: Multi-Dimensional Evaluation of Tool-Augmented Dialogue](https://md.research.elamur.ai/free/en/papers/shourya-2026-when-users-are-happy-but/) [Workshop on Generation, Evaluation and Metrics (GEM)](https://md.research.elamur.ai/free/en/venues/gem/)**Tanya Shourya, Yingfan Wang, Zhaoyi Joey Hou, et al.*2026*
46. [**Survey of Tool Use in Large Language Models (大语言模型的工具使用综述) Acta Automatica Sinica (自动化学报)**Yining Zheng (郑逸宁), Zhen Yu (余镇), Bufan Li (李不凡), et al.*2025*](https://md.research.elamur.ai/free/en/papers/zheng-2025-tool-use-large/)

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