Who cites Benedikt Stroebl
- MLE-bench: Evaluating Machine Learning Agents on Machine Learning EngineeringarXiv:2410.07095Jun Shern Chan, Neil Chowdhury, Oliver Jaffe, et al.2024 · 140 citations
- Why Do Multi-Agent LLM Systems Fail?arXiv:2503.13657Mert Cemri, Melissa Z. Pan, Shuyi Yang, et al.2025 · 89 citations
- PaperBench: Evaluating AI's Ability to Replicate AI ResearcharXiv:2504.01848Giulio Starace, Oliver Jaffe, Dane Sherburn, et al.2025 · 86 citations
- More Agents Is All You NeedarXiv:2402.05120Junyou Li, Qin Zhang, Yangbin Yu, et al.2024 · 85 citations
- ScienceAgentBench: Toward Rigorous Assessment of Language Agents for Data-Driven Scientific DiscoveryarXiv:2410.05080Ziru Chen, Shijie Chen, Yuting Ning, et al.2024 · 81 citations
- RLEF: Grounding Code LLMs in Execution Feedback with Reinforcement LearningarXiv:2410.02089Jonas Gehring, Kunhao Zheng, Jade Copet, et al.2024 · 51 citations
- A Survey on Evaluation of LLM-based AgentsFindings of the Association for Computational LinguisticsAsaf Yehudai, Lilach Eden, Alan Li, et al.2026 · 21 citations
- Examining False Positives under Inference Scaling for Mathematical ReasoningConference on Empirical Methods in Natural Language Processing (EMNLP)Yu Wang, Nan Yang, Liang Wang, et al.2025 · 9 citations
- Localized Cultural Knowledge is Conserved and Controllable in Large Language ModelsFindings of the Association for Computational LinguisticsVeniamin Veselovsky, Berke Argın, Benedikt Stroebl, et al.2026 · 7 citations
- When Life Gives You Samples: The Benefits of Scaling up Inference Compute for Multilingual LLMsConference on Empirical Methods in Natural Language Processing (EMNLP)Ammar Khairi, Daniel D'souza, Ye Shen, et al.2025 · 6 citations
- Uncertainty Quantification in LLM Agents: Foundations, Emerging Challenges, and OpportunitiesAnnual Meeting of the Association for Computational Linguistics (ACL)Changdae Oh, Seongheon Park, To Eun Kim, et al.2026 · 4 citations
- SafeSearch: Do Not Trade Safety for Utility in LLM Search AgentsFindings of the Association for Computational LinguisticsQiusi Zhan, Angeline Budiman-Chan, Abdelrahman Zayed, et al.2026 · 1 citation
- Agentic CLEAR: Automating Multi-Level Evaluation of LLM AgentsAnnual Meeting of the Association for Computational Linguistics (ACL)Asaf Yehudai, Lilach Eden, Michal Shmueli-Scheuer2026
- Efficient Agent Evaluation via Diversity-Guided User SimulationAnnual Meeting of the Association for Computational Linguistics (ACL)Itay Nakash, George Kour, Ateret Anaby Tavor2026
- Follow the Path: Reasoning over Knowledge Graph Paths to Improve Large Language Model FactualityFindings of the Association for Computational LinguisticsMike Zhang, Johannes Bjerva, Russa Biswas2026
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