---
title: "Who cites Sunhao Dai — 110 papers of our library"
description: "110 papers of the Elamur Research library cite the works of Sunhao Dai, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/sunhao-dai/cited-by/"
---
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# Who cites Sunhao Dai

110 citations of their works from 110 papers of our library (of the 149,439 whose bibliographies we read) · 35 with a page here, the most cited first · [← Sunhao Dai](https://md.research.elamur.ai/free/en/authors/sunhao-dai/)

1. [**Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters arXiv:2408.03314**Charlie Snell, Jaehoon Lee, Kelvin Xu, et al.*2024 · 567 citations*](https://md.research.elamur.ai/free/en/papers/snell-2024-scaling-llm-test-time-compute/)
2. [**Tulu 3: Pushing Frontiers in Open Language Model Post-Training arXiv:2411.15124**Nathan Lambert, Jacob Morrison, Valentina Pyatkin, et al.*2024 · 423 citations*](https://md.research.elamur.ai/free/en/papers/lambert-2024-tulu-3-pushing-frontiers-open/)
3. [**Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning arXiv:2503.09516**Bowen Jin, Hansi Zeng, Zhenrui Yue, et al.*2025 · 322 citations*](https://md.research.elamur.ai/free/en/papers/jin-2025-search-r1-training-llms-reason/)
4. [**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/)
5. [**Automated Design of Agentic Systems arXiv:2408.08435**Shengran Hu, Cong Lu, Jeff Clune*2024 · 89 citations*](https://md.research.elamur.ai/free/en/papers/hu-2024-automated-design-agentic-systems/)
6. [**A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and Beyond arXiv:2503.21614**Xiaoye Qu, Yafu Li, Zhao-Chen Su, et al.*2025 · 55 citations*](https://md.research.elamur.ai/free/en/papers/qu-2025-survey-efficient-reasoning-large-reasoning/)
7. **[StepSearch: Igniting LLMs Search Ability via Step-Wise Proximal Policy Optimization](https://md.research.elamur.ai/free/en/papers/zheng-2025-stepsearch-igniting-llms-search-ability/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xuhui Zheng, Kang An, Ziliang Wang, et al.*2025 · 19 citations*
8. **[Adaptive Tool Use in Large Language Models with Meta-Cognition Trigger](https://md.research.elamur.ai/free/en/papers/li-2025-adaptive-tool-use-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenjun Li, Dexun Li, Kuicai Dong, et al.*2025 · 16 citations*
9. **[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*
10. **[Understanding LLM Reasoning for Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/yuan-2026-understanding-llm-reasoning-abstractive-summarization/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haohan Yuan, Haopeng Zhang*2026 · 11 citations*
11. **[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*
12. **[A Survey of Inductive Reasoning for Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2026-survey-inductive-reasoning-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kedi Chen, Dezhao Ruan, Yuhao Dan, et al.*2026 · 10 citations*
13. **[Android Coach: Improve Online Agentic Training Efficiency with Single State Multiple Actions](https://md.research.elamur.ai/free/en/papers/gan-2026-android-coach-improve-online-agentic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guo Gan, Yuxuan Ding, Cong Chen, et al.*2026 · 7 citations*
14. **[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*
15. **[EVOTOOL: Self-Evolving Tool-Use Policy Optimization in LLM Agents via Blame-Aware Mutation and Diversity-Aware Selection](https://md.research.elamur.ai/free/en/papers/yang-2026-evotool-self-evolving-tool-use/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shuo Yang, Caren Han, Xueqi Ma, et al.*2026 · 6 citations*
16. **[Feedback-Driven Tool-Use Improvements in Large Language Models via Automated Build Environments](https://md.research.elamur.ai/free/en/papers/ye-2026-feedback-driven-tool-use-improvements/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Junjie Ye, Changhao Jiang, Zhengyin Du, et al.*2026 · 6 citations*
17. **[LoopTool: Closing the Data–Training Loop for Robust LLM Tool Calls](https://md.research.elamur.ai/free/en/papers/zhang-2026-looptool-closing-data-training-loop/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kangning Zhang, Weiwen Liu, Wenxiang Jiao, et al.*2026 · 6 citations*
18. **[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*
19. **[LLM Agents in Law: Taxonomy, Applications, and Challenges](https://md.research.elamur.ai/free/en/papers/liu-2026-llm-agents-law-taxonomy-applications/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shuang Liu, Ruijia Zhang, Ruoyun Ma, et al.*2026 · 4 citations*
20. **[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*
21. **[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*
22. **[LexGenius: An Expert-Level Benchmark for Large Language Models in Legal General Intelligence](https://md.research.elamur.ai/free/en/papers/liu-2026-lexgenius-expert-level-benchmark-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenjin Liu, Haoran Luo, Xin Feng, et al.*2026 · 2 citations*
23. **[Attribution, Citation, and Quotation: A Survey of Evidence-based Text Generation with Large Language Models](https://md.research.elamur.ai/free/en/papers/schreieder-2026-attribution-citation-quotation-survey-evidence/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tobias Schreieder, Tim Schopf, Michael Färber*2026 · 1 citation*
24. **[MatchTIR: Fine-Grained Supervision for Tool-Integrated Reasoning via Bipartite Matching](https://md.research.elamur.ai/free/en/papers/qu-2026-matchtir-fine-grained-supervision-tool/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Changle Qu, Sunhao Dai, Hengyi Cai, et al.*2026 · 1 citation*
25. **[SepSeq: A Training-Free Framework for Long Numerical Sequence Processing in LLMs](https://md.research.elamur.ai/free/en/papers/sun-2026-sepseq-training-free-framework-long/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jie Sun, Yu Liu, Lu Han, et al.*2026 · 1 citation*
26. **[ToolDreamer: Instilling LLM Reasoning Into Tool Retrievers](https://md.research.elamur.ai/free/en/papers/sengupta-2026-tooldreamer-instilling-llm-reasoning-into/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Saptarshi Sengupta, Zhengyu Zhou, Jun Araki, et al.*2026 · 1 citation*
27. **[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*
28. **[Beyond Static Toolsets: Self-Evolving LLM Tool Agents via Continual Documentation Adaptation](https://md.research.elamur.ai/free/en/papers/wu-2026-beyond-static-toolsets-self-evolving/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Bin Wu, Edgar Meij, Emine Yilmaz*2026*
29. [**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/)
30. **[EvoMemKG: An Evolvable Memory Agent for Multi-hop Knowledge Graph Reasoning](https://md.research.elamur.ai/free/en/papers/tian-2026-evomemkg-evolvable-memory-agent-multi/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shiyu Tian, Shuyue Xing, Zhuoxin Han, et al.*2026*
31. **[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*
32. **[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*
33. **[Harnessing the Latent Space: From Steering Vectors to Model Calibrators for Control and Trust](https://md.research.elamur.ai/free/en/papers/subramani-2026-harnessing-latent-space-steering-vectors/) [Big Picture v2: Crafting a Research Narrative](https://md.research.elamur.ai/free/en/venues/bigpicture/)**Nishant Subramani*2026*
34. **[SGA-MCTS: Decoupling Planning from Execution via Training-Free Atomic Experience Retrieval](https://md.research.elamur.ai/free/en/papers/xie-2026-sga-mcts-decoupling-planning-execution/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xin Xie, Dongyun Xue, Wuguannan Yao, et al.*2026*
35. **[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*

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

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