---
title: "Who cites Timo Kaufmann — 63 papers of our library"
description: "63 papers of the Elamur Research library cite the works of Timo Kaufmann, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/timo-kaufmann/cited-by/"
---
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# Who cites Timo Kaufmann

63 citations of their works from 63 papers of our library (of the 149,439 whose bibliographies we read) · 24 with a page here, the most cited first · [← Timo Kaufmann](https://md.research.elamur.ai/free/en/authors/timo-kaufmann/)

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. [**HybridFlow: A Flexible and Efficient RLHF Framework arXiv:2409.19256**Guangming Sheng, Chi Zhang, Zilingfeng Ye, et al.*2024 · 624 citations*](https://md.research.elamur.ai/free/en/papers/sheng-2024-hybridflow-flexible-efficient-rlhf-framework/)
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. [**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/)
5. [**Secrets of RLHF in Large Language Models Part II: Reward Modeling arXiv:2401.06080**Binghai Wang, Rui Zheng, Lu Chen, et al.*2024 · 72 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-secrets-rlhf-large-language-models/)
6. **[Safer or Luckier? LLMs as Safety Evaluators Are Not Robust to Artifacts](https://md.research.elamur.ai/free/en/papers/chen-2025-safer-or-luckier-llms-as/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hongyu Chen, Seraphina Goldfarb-Tarrant*2025 · 13 citations*
7. **[LLM-Based Human-Agent Collaboration and Interaction Systems: A Survey](https://md.research.elamur.ai/free/en/papers/zou-2026-llm-based-human-agent-collaboration/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Henry Peng Zou, Wei-Chieh Huang, Yaozu Wu, et al.*2026 · 12 citations*
8. [**EventRL: Enhancing Event Extraction with Outcome Supervision for Large Language Models arXiv:2402.11430**Jun Gao, Huan Zhao, Wei Wang, et al.*2024 · 11 citations*](https://md.research.elamur.ai/free/en/papers/gao-2024-eventrl-enhancing-event-extraction-outcome/)
9. **[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*
10. **[Automatic Reviewers Fail to Detect Faulty Reasoning in Research Papers: A New Counterfactual Evaluation Framework](https://md.research.elamur.ai/free/en/papers/dycke-2026-automatic-reviewers-fail-detect-faulty/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Nils Dycke, Iryna Gurevych*2026 · 5 citations*
11. **[Can LLMs Automate Fact-Checking Article Writing?](https://md.research.elamur.ai/free/en/papers/sahnan-2026-can-llms-automate-fact-checking/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Dhruv Sahnan, David Corney, Irene Larraz, et al.*2026 · 5 citations*
12. **[AutoGraph-R1: End-to-End Reinforcement Learning for Knowledge Graph Construction](https://md.research.elamur.ai/free/en/papers/tsang-2026-autograph-r1-end-end-reinforcement/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hong Ting Tsang, Jiaxin Bai, Haoyu Huang, et al.*2026 · 4 citations*
13. **[ProMed: Shapley Information Gain Guided Reinforcement Learning for Proactive Medical LLMs](https://md.research.elamur.ai/free/en/papers/ding-2026-promed-shapley-information-gain-guided/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hongxin Ding, Baixiang Huang, Yue Fang, et al.*2026 · 4 citations*
14. **[OpenGenAlign: A Preference Dataset and Benchmark for Trustworthy Reward Modeling in Open-Ended, Long-Context Generation](https://md.research.elamur.ai/free/en/papers/zhang-2026-opengenalign-preference-dataset-benchmark-trustworthy/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hanning Zhang, Juntong Song, Juno Zhu, et al.*2026 · 2 citations*
15. **[Position: From Noise to Signal to Selbstzweck - Reframing Human Label Variation in the Era of Post-training in NLP](https://md.research.elamur.ai/free/en/papers/xu-2026-position-noise-signal-selbstzweck-reframing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shanshan Xu, Santosh T.Y.S.S, Barbara Plank*2026 · 1 citation*
16. **[CARL: Constraint-Aware Reinforcement Learning for Planning with LLMs](https://md.research.elamur.ai/free/en/papers/qi-2026-carl-constraint-aware-reinforcement-learning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qiuyi Qi, Jinjian Zhang, Mutian Bao, et al.*2026*
17. **[From Answers to Arguments: Toward Trustworthy Clinical Diagnostic Reasoning with Toulmin-Guided Curriculum Goal-Conditioned Learning](https://md.research.elamur.ai/free/en/papers/zhan-2026-answers-arguments-trustworthy-clinical-diagnostic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chen Zhan, Xiaoyu Tan, Gengchen Ma, et al.*2026*
18. **[Improving LLM Domain Certification with Pretrained Guide Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-improving-llm-domain-certification-pretrained/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Jiaqian Zhang, Zhaozhi Qian, Faroq AL-Tam, et al.*2026*
19. **[Joint Optimization of Training Data and Policy in RLHF](https://md.research.elamur.ai/free/en/papers/yu-2026-joint-optimization-training-data-policy/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhuohao Yu, Jiali Zeng, Weizheng Gu, et al.*2026*
20. **[Nanda Family: Open-Weights Generative Large Language Models for Hindi](https://md.research.elamur.ai/free/en/papers/singh-2026-nanda-family-open-weights-generative/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Aaryamonvikram Singh, Debopriyo Banerjee, Dhruv Sahnan, et al.*2026*
21. **[NITI: Neural Plan Concretization for Incremental Execution, Bridging and Trigger Inference from Underspecified Human Policies](https://md.research.elamur.ai/free/en/papers/banerjee-2026-niti-neural-plan-concretization-incremental/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ayan Banerjee, Shomrik Barua Banerjee, Sandeep Gupta*2026*
22. **[PARL: Prompt-based Agents for Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/resendiz-2026-parl-prompt-based-agents-reinforcement/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Yarik Menchaca Resendiz, Roman Klinger*2026*
23. **[See2Refine: Vision-Language Feedback Improves LLM-Based eHMI Action Designers](https://md.research.elamur.ai/free/en/papers/xia-2026-see2refine-vision-language-feedback-improves/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ding Xia, Xinyue Gui, Mark Colley, et al.*2026*
24. **[Too Open for Opinion? Embracing Open-Endedness in Large Language Models for Social Simulation](https://md.research.elamur.ai/free/en/papers/ma-2026-too-open-opinion-embracing-open/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Bolei Ma, Yong Cao, Indira Sen, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/authors/timo-kaufmann/) — Timo Kaufmann