---
title: "Who cites Yingxiu Zhao — 193 papers of our library"
description: "193 papers of the Elamur Research library cite the works of Yingxiu Zhao, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/yingxiu-zhao/cited-by/"
---
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# Who cites Yingxiu Zhao

193 citations of their works from 193 papers of our library (of the 149,439 whose bibliographies we read) · 59 with a page here, the most cited first · [← Yingxiu Zhao](https://md.research.elamur.ai/free/en/authors/yingxiu-zhao/)

1. [**The Llama 3 Herd of Models arXiv:2407.21783**Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri, et al.*2024 · 7,682 citations*](https://md.research.elamur.ai/free/en/papers/grattafiori-2024-llama-3-herd-models/)
2. [**Large Language Model based Multi-Agents: A Survey of Progress and Challenges arXiv:2402.01680**Taicheng Guo, Xiuying Chen, Yaqi Wang, et al.*2024 · 288 citations*](https://md.research.elamur.ai/free/en/papers/guo-2024-large-language-model-based/)
3. [**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/)
4. [**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/)
5. **[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*
6. [**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/)
7. [**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/)
8. **[R-Judge: Benchmarking Safety Risk Awareness for LLM Agents](https://md.research.elamur.ai/free/en/papers/yuan-2024-r-judge-benchmarking-safety-risk/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tongxin Yuan, Zhiwei He, Lingzhong Dong, et al.*2024 · 106 citations*
9. [**ToolACE: Winning the Points of LLM Function Calling arXiv:2409.00920**Weiwen Liu; Xu Huang; Xingshan Zeng; Xinlong Hao; Shuai Yu; Dexun Li; Shuai Wang; Weinan Gan; Zhengying Liu; Yuanqing Yu; Zezhong Wang; Yuxian Wang; Wu Ning; Yutai Hou; Bin Wang; Chuhan Wu; Xinzhi Wang; Yong Liu; Yasheng Wang; Duyu Tang; Dandan Tu; Lifeng Shang; Xin Jiang; Ruiming Tang; Defu Lian; Qun Liu;, Enhong Chen*2024 · 101 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-toolace-winning-points-llm-function/)
10. [**ToolRL: Reward is All Tool Learning Needs arXiv:2504.13958**Cheng Qian, Emre Can Acikgoz, Qi He, et al.*2025 · 94 citations*](https://md.research.elamur.ai/free/en/papers/qian-2025-toolrl-reward-all-tool-learning/)
11. [**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/)
12. **[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*
13. **[ToolSandbox: A Stateful, Conversational, Interactive Evaluation Benchmark for LLM Tool Use Capabilities](https://md.research.elamur.ai/free/en/papers/lu-2025-toolsandbox-stateful-conversational-interactive-evaluation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiarui Lu, Thomas Holleis, Yizhe Zhang, et al.*2025 · 70 citations*
14. **[xLAM: A Family of Large Action Models to Empower AI Agent Systems](https://md.research.elamur.ai/free/en/papers/zhang-2025-xlam-family-large-action-models/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Jianguo Zhang, Tian Lan, Ming Zhu, et al.*2025 · 68 citations*
15. **[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*
16. **[HiAgent: Hierarchical Working Memory Management for Solving Long-Horizon Agent Tasks with Large Language Model](https://md.research.elamur.ai/free/en/papers/hu-2025-hiagent-hierarchical-working-memory-management/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mengkang Hu, Tianxing Chen, Qiguang Chen, et al.*2025 · 49 citations*
17. **[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*
18. **[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*
19. [**GameBench: Evaluating Strategic Reasoning Abilities of LLM Agents arXiv:2406.06613**Anthony Costarelli, Mat Allen, Roman Hauksson, et al.*2024 · 20 citations*](https://md.research.elamur.ai/free/en/papers/costarelli-2024-gamebench-evaluating-strategic-reasoning-abilities/)
20. [**MindSearch: Mimicking Human Minds Elicits Deep AI Searcher arXiv:2407.20183**Zehui Chen, Kuikun Liu, Qiuchen Wang, et al.*2024 · 20 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-mindsearch-mimicking-human-minds-elicits/)
21. **[Self-Correcting RAG: Enhancing Faithfulness via MMKP Context Selection and NLI-Guided MCTS](https://md.research.elamur.ai/free/en/papers/xu-2026-self-correcting-rag-enhancing-faithfulness/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shijia Xu, Zhou Wu, Xiaolong Jia, et al.*2026 · 15 citations*
22. **[ToolHop: A Query-Driven Benchmark for Evaluating Large Language Models in Multi-Hop Tool Use](https://md.research.elamur.ai/free/en/papers/ye-2025-toolhop-query-driven-benchmark-evaluating/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junjie Ye, Zhengyin Du, Xuesong Yao, et al.*2025 · 15 citations*
23. **[Can a Single Model Master Both Multi-turn Conversations and Tool Use? CoALM: A Unified Conversational Agentic Language Model](https://md.research.elamur.ai/free/en/papers/acikgoz-2025-can-single-model-master-both/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Emre Can Acikgoz, Jeremiah Greer, Akul Datta, et al.*2025 · 13 citations*
24. **[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*
25. **[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*
26. [**Hunyuan-TurboS: Advancing Large Language Models through Mamba-Transformer Synergy and Adaptive Chain-of-Thought arXiv:2505.15431**Tencent Hunyuan Team, Ao Liu, Botong Zhou, et al.*2025 · 10 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-hunyuan-hunyuan-turbos-advancing-large/)
27. **[Planning with Multi-Constraints via Collaborative Language Agents](https://md.research.elamur.ai/free/en/papers/zhang-2025-planning-multi-constraints-collaborative-language/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Cong Zhang, Xin Deik Goh, Dexun Li, et al.*2025 · 10 citations*
28. [**DeepSeek-OCR 2: Visual Causal Flow arXiv:2601.20552**Haoran Wei, Yaofeng Sun, Yukun Li*2026 · 8 citations*](https://md.research.elamur.ai/free/en/papers/wei-2026-deepseek-ocr-2-visual/)
29. **[LogicPro: Improving Complex Logical Reasoning via Program-Guided Learning](https://md.research.elamur.ai/free/en/papers/jiang-2025-logicpro-improving-complex-logical-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jin Jiang, Yuchen Yan, Yang Liu, et al.*2025 · 8 citations*
30. **[DEBATE, TRAIN, EVOLVE: Self-Evolution of Language Model Reasoning](https://md.research.elamur.ai/free/en/papers/srivastava-2025-debate-train-evolve-self-evolution/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Gaurav Srivastava, Zhenyu Bi, Meng Lu, et al.*2025 · 7 citations*
31. **[NesTools: A Dataset for Evaluating Nested Tool Learning Abilities of Large Language Models](https://md.research.elamur.ai/free/en/papers/han-2025-nestools-dataset-evaluating-nested-tool/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Han Han, Tong Zhu, Xiang Zhang, et al.*2025 · 7 citations*
32. **[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*
33. **[EnvScaler: Scaling Tool-Interactive Environments for LLM Agent via Programmatic Synthesis](https://md.research.elamur.ai/free/en/papers/song-2026-envscaler-scaling-tool-interactive-environments/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiaoshuai Song, Haofei Chang, Guanting Dong, et al.*2026 · 5 citations*
34. **[Uncertainty Quantification in LLM Agents: Foundations, Emerging Challenges, and Opportunities](https://md.research.elamur.ai/free/en/papers/oh-2026-uncertainty-quantification-llm-agents-foundations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Changdae Oh, Seongheon Park, To Eun Kim, et al.*2026 · 4 citations*
35. **[Beyond Accuracy: Unveiling Inefficiency Patterns in Tool-Integrated Reasoning](https://md.research.elamur.ai/free/en/papers/su-2026-beyond-accuracy-unveiling-inefficiency-patterns/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qisheng Su, Shiting Huang, Zhen Fang, et al.*2026 · 2 citations*
36. **[Failure makes the agent stronger: Enhancing Accuracy through Structured Reflection for Reliable Tool Interactions](https://md.research.elamur.ai/free/en/papers/su-2026-failure-makes-agent-stronger-enhancing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Junhao Su, Yuanliang Wan, Junwei Yang, et al.*2026 · 2 citations*
37. **[MedMCP-Calc: Benchmarking LLMs for Realistic Medical Calculator Scenarios via MCP Integration](https://md.research.elamur.ai/free/en/papers/zhu-2026-medmcp-calc-benchmarking-llms-realistic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yakun Zhu, Yutong Huang, Shengqian Qin, et al.*2026 · 2 citations*
38. **[Trajectory2Task: Training Robust Tool-Calling Agents with Synthesized Yet Verifiable Data for Complex User Intents](https://md.research.elamur.ai/free/en/papers/wang-2026-trajectory2task-training-robust-tool-calling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziyi Wang, Yuxuan Lu, Yimeng Zhang, et al.*2026 · 2 citations*
39. **[Tool Calling for Arabic LLMs: Data Strategies and Instruction Tuning](https://md.research.elamur.ai/free/en/papers/ersoy-2025-tool-calling-arabic-llms-data/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Asım Ersoy, Enes Altinisik, Kareem Mohamed Darwish, et al.*2025 · 2 citations*
40. **[A Survey on LLM-based Conversational User Simulation](https://md.research.elamur.ai/free/en/papers/ni-2026-survey-llm-based-conversational-user/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Bo Ni, Yu Wang, Leyao Wang, et al.*2026 · 1 citation*
41. **[TEA-Bench: A Systematic Benchmarking of Tool-enhanced Emotional Support Dialogue Agent](https://md.research.elamur.ai/free/en/papers/sui-2026-tea-bench-systematic-benchmarking-tool/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xingyu Sui, Yanyan Zhao, Yulin Hu, et al.*2026 · 1 citation*
42. **[AJ-Bench: Benchmarking Agent-as-a-Judge for Environment-Aware Evaluation](https://md.research.elamur.ai/free/en/papers/shi-2026-aj-bench-benchmarking-agent-as/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wentao Shi, Yu Wang, Yuyang Zhao, et al.*2026*
43. **[ARCHITECT: Uncertainty-Aware Dynamic Tool Learning via Causal Intervention for Open-World Agents](https://md.research.elamur.ai/free/en/papers/wang-2026-architect-uncertainty-aware-dynamic-tool/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhangyi Wang, Jiexiang Xu, Bingnan Yu, et al.*2026*
44. **[Assertion-Conditioned Compliance: A Provenance-Aware Vulnerability in Multi-Turn Tool-Calling Agents](https://md.research.elamur.ai/free/en/papers/waqas-2026-assertion-conditioned-compliance-provenance-aware/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Daud Waqas, Aaryamaan Golthi, Erika Hayashida, et al.*2026*
45. **[C-World: A Computer Use Agent Environment Creator](https://md.research.elamur.ai/free/en/papers/xi-2026-c-world-computer-use-agent/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziqiao Xi, Shuang Liang, Qi Liu, et al.*2026*
46. **[DaMo: Data Mixing Optimizer in Fine-tuning Multimodal LLMs for Mobile Phone Agents](https://md.research.elamur.ai/free/en/papers/shi-2026-damo-data-mixing-optimizer-fine/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kai Shi, Jun Yang, Ni Yang, et al.*2026*
47. [**English is Not All You Need: Systematically Exploring the Role of Multilinguality in LLM Post-Training arXiv:2604.13286**Mehak Dhaliwal, Shashwat Chaurasia, Yao Qin, et al.*2026*](https://md.research.elamur.ai/free/en/papers/dhaliwal-2026-english-all-need-systematically-exploring/)
48. **[FAMA: Failure-Aware Meta-Agentic Framework for Open-Source LLMs in Interactive Tool Use Environments](https://md.research.elamur.ai/free/en/papers/saeidi-2026-fama-failure-aware-meta-agentic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Amir Saeidi, Venkatesh Mishra, Souradeep Mukhopadhyay, et al.*2026*
49. **[GenesisFunc: Multi-Agent Data Generation for Accurate and Generalizable Function-Calling](https://md.research.elamur.ai/free/en/papers/xu-2026-genesisfunc-multi-agent-data-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao-Xiang Xu, Chong Deng, Jiaqing Liu, et al.*2026*
50. **[Knowledge is Not Enough: Injecting RL Skills for Continual Adaptation](https://md.research.elamur.ai/free/en/papers/tang-2026-knowledge-is-not-enough-injecting/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Pingzhi Tang, Yiding Wang, Muhan Zhang*2026*
51. **[QuantumQA: Enhancing Scientific Reasoning via Physics-Consistent Dataset and Verification-Aware Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/qu-2026-quantumqa-enhancing-scientific-reasoning-physics/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Songxin Qu, Tai-Ping Sun, Yun-Jie Wang, et al.*2026*
52. **[RV-Syn: Rational and Verifiable Mathematical Reasoning Data Synthesis based on Structured Function Library](https://md.research.elamur.ai/free/en/papers/wang-2026-rv-syn-rational-verifiable-mathematical/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiapeng Wang, Jinhao Jiang, Zhiqiang Zhang, et al.*2026*
53. **[SGVEF-LOOP: Coverage-Guided Progressive Topological Exploration and Fact-Grounded Metamorphic Evaluation for MCP Agents](https://md.research.elamur.ai/free/en/papers/liu-2026-sgvef-loop-coverage-guided-progressive/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zenghao Liu, Yansong Zhang*2026*
54. **[Thesis Proposal: When Does an Agent Know It Is Lost? Confidence Trajectory Analysis for Tool-Using LLMs](https://md.research.elamur.ai/free/en/papers/mao-2026-thesis-proposal-when-does-agent/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhenjiang Mao*2026*
55. **[Tool-Aware Planning for Contact-Center Analytics: Evaluating LLMs through Lineage-Guided Query Decomposition](https://md.research.elamur.ai/free/en/papers/nathan-2026-tool-aware-planning-contact-center/) [Workshop on Generation, Evaluation and Metrics (GEM)](https://md.research.elamur.ai/free/en/venues/gem/)**Varun Nathan, Shreyas Guha, Ayush Kumar*2026*
56. **[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*
57. **[Training Verifier to Assessing Complex Real-World Tool-Use Trajectories](https://md.research.elamur.ai/free/en/papers/sun-2026-training-verifier-assessing-complex-real/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Linzhuang Sun, Mingyang Chen, Hao Liang, et al.*2026*
58. **[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*
59. [**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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