--- title: "Who cites DISCOVERYWORLD: A Virtual — 36 citing papers" description: "36 papers of the Elamur Research library cite «DISCOVERYWORLD: A Virtual Environment for Developing and Evaluating Automated…" canonical: "https://research.elamur.ai/free/en/papers/jansen-2024-discoveryworld-virtual-environment-developing/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/jansen-2024-discoveryworld-virtual-environment-developing/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [DISCOVERYWORLD: A Virtual Environment for…](https://md.research.elamur.ai/free/en/papers/jansen-2024-discoveryworld-virtual-environment-developing/) / cited by # Who cites «DISCOVERYWORLD: A Virtual Environment for Developing and Evaluating Automated Scientific Discovery Agents» 36 papers of our library cite it (of the 149,439 whose bibliographies we read) · 18 with a page here, the most cited first · [← back to «DISCOVERYWORLD: A Virtual Environment for Developing and Evaluating Automated Scientific Discovery Agents»](https://md.research.elamur.ai/free/en/papers/jansen-2024-discoveryworld-virtual-environment-developing/) 1. [**PaperBench: Evaluating AI's Ability to Replicate AI Research arXiv:2504.01848**Giulio Starace, Oliver Jaffe, Dane Sherburn, et al.*2025 · 86 citations*](https://md.research.elamur.ai/free/en/papers/starace-2025-paperbench-evaluating-ai-s/) 2. [**MLGym: A New Framework and Benchmark for Advancing AI Research Agents arXiv:2502.14499**Deepak Nathani, Lovish Madaan, Nicholas Roberts, et al.*2025 · 50 citations*](https://md.research.elamur.ai/free/en/papers/nathani-2025-mlgym-new-framework-benchmark/) 3. [**Agent-as-a-Judge: Evaluate Agents with Agents arXiv:2410.10934**Mingchen Zhuge, Changsheng Zhao, Dylan Ashley, et al.*2024 · 50 citations*](https://md.research.elamur.ai/free/en/papers/zhuge-2024-agent-judge-evaluate-agents/) 4. [**RE-Bench: Evaluating frontier AI R&D capabilities of language model agents against human experts arXiv:2411.15114**Hjalmar Wijk, Tao Lin, Joel Becker, et al.*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/wijk-2024-re-bench-evaluating-frontier/) 5. [**AgentRxiv: Towards Collaborative Autonomous Research arXiv:2503.18102**Samuel Schmidgall, Michael Moor*2025 · 39 citations*](https://md.research.elamur.ai/free/en/papers/schmidgall-2025-agentrxiv-collaborative-autonomous-research/) 6. **[From Automation to Autonomy: A Survey on Large Language Models in Scientific Discovery](https://md.research.elamur.ai/free/en/papers/zheng-2025-automation-autonomy-survey-large/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tianshi Zheng, Zheye Deng, Hong Ting Tsang, et al.*2025 · 39 citations* 7. [**LLM4SR: A Survey on Large Language Models for Scientific Research arXiv:2501.04306**Ziming Luo, Zonglin Yang, Zexin Xu, et al.*2025 · 39 citations*](https://md.research.elamur.ai/free/en/papers/luo-2025-llm4sr-survey-large-language/) 8. [**CodeScientist: End-to-End Semi-Automated Scientific Discovery with Code-based Experimentation arXiv:2503.22708 · ACL 2025 (Findings)**Peter Jansen, Oyvind Tafjord, Marissa Radensky, et al.*2025 · 31 citations*](https://md.research.elamur.ai/free/en/papers/jansen-2025-codescientist-end-end-semi/) 9. [**Towards Scientific Intelligence: A Survey of LLM-based Scientific Agents arXiv:2503.24047**Shuo Ren, Can Xie, Pu Jian, et al.*2025 · 24 citations*](https://md.research.elamur.ai/free/en/papers/ren-2025-scientific-intelligence-survey-llm/) 10. **[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* 11. **[AI4Research: A Survey of Artificial Intelligence for Scientific Research](https://md.research.elamur.ai/free/en/papers/chen-2025-ai4research-survey-artificial-intelligence/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Mingda Yang, Libo Qin, et al.*2025 · 21 citations* 12. [**From AI for Science to Agentic Science: A Survey on Autonomous Scientific Discovery arXiv:2508.14111**Jiaqi Wei, Yuejin Yang, Xiang Zhang, et al.*2025 · 19 citations*](https://md.research.elamur.ai/free/en/papers/wei-2025-ai-science-agentic-science/) 13. [**Aviary: training language agents on challenging scientific tasks arXiv:2412.21154**Siddharth Narayanan, James D. Braza, Ryan-Rhys Griffiths, et al.*2024 · 18 citations*](https://md.research.elamur.ai/free/en/papers/narayanan-2024-aviary-training-language-agents/) 14. [**Sparks of Science: Hypothesis Generation Using Structured Paper Data arXiv:2504.12976**Charles O'Neill, Tirthankar Ghosal, Roberta R\uaileanu, et al.*2025 · 16 citations*](https://md.research.elamur.ai/free/en/papers/o-neill-2025-sparks-science-hypothesis-generation-using/) 15. **[Automated Scientific Discovery: From Equation Discovery to Autonomous Discovery Systems](https://md.research.elamur.ai/free/en/papers/kramer-2023-automated-scientific-discovery-equation/) [Machine Learning](https://md.research.elamur.ai/free/en/venues/machine-learning/)**Stefan Kramer, Mattia Cerrato, Jannis Brugger, et al.*2023 · 13 citations* 16. **[Literature Meets Data: A Synergistic Approach to Hypothesis Generation](https://md.research.elamur.ai/free/en/papers/liu-2025-literature-meets-data-synergistic-approach/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haokun Liu, Yangqiaoyu Zhou, Mingxuan Li, et al.*2025 · 12 citations* 17. [**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/) 18. [**Position: Correct Answer, Wrong Mechanism — When AI Scientists Defend General Claims Their Own Data Contradicts arXiv:2606.23175**Steven Young Eulig*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/eulig-2026-position-correct-answer-wrong/) 18 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/jansen-2024-discoveryworld-virtual-environment-developing/) — DISCOVERYWORLD: A Virtual Environment for Developing and Evaluating Automated Scientific Discovery Agents