--- title: "Who cites A Systematic Survey and Critical — 41 citing papers" description: "41 papers of the Elamur Research library cite «A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges…" canonical: "https://research.elamur.ai/free/en/papers/laskar-2024-systematic-survey-critical-review-evaluating/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/laskar-2024-systematic-survey-critical-review-evaluating/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [A Systematic Survey and Critical Review on…](https://md.research.elamur.ai/free/en/papers/laskar-2024-systematic-survey-critical-review-evaluating/) / cited by # Who cites «A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and Recommendations» 41 papers of our library cite it (of the 149,439 whose bibliographies we read) · 11 with a page here, the most cited first · [← back to «A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and Recommendations»](https://md.research.elamur.ai/free/en/papers/laskar-2024-systematic-survey-critical-review-evaluating/) 1. **[CFBench: A Comprehensive Constraints-Following Benchmark for LLMs](https://md.research.elamur.ai/free/en/papers/zhang-2025-cfbench-comprehensive-constraints-following-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tao Zhang, ChengLIn Zhu, Yanjun Shen, et al.*2025 · 30 citations* 2. **[PPTAgent: Generating and Evaluating Presentations Beyond Text-to-Slides](https://md.research.elamur.ai/free/en/papers/zheng-2025-pptagent-generating-evaluating-presentations-beyond/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Hao Zheng, Xinyan Guan, Hao Kong, et al.*2025 · 30 citations* 3. **[Which of These Best Describes Multiple Choice Evaluation with LLMs? A) Forced B) Flawed C) Fixable D) All of the Above](https://md.research.elamur.ai/free/en/papers/balepur-2025-which-these-best-describes-multiple/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nishant Balepur, Rachel Rudinger, Jordan Boyd-Graber*2025 · 28 citations* 4. **[LLMEval-Fair: A Large-Scale Longitudinal Study on Robust and Fair Evaluation of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-llmeval-fair-large-scale-longitudinal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ming Zhang, Yujiong Shen, Jingyi Deng, et al.*2026 · 3 citations* 5. **[Adaptive Data Flywheel: Applying MAPE Control Loops to AI Agent Improvement](https://md.research.elamur.ai/free/en/papers/shukla-2026-adaptive-data-flywheel-applying-mape/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Aaditya Shukla, Sidney Knowles, Meenakshi Madugula, et al.*2026 · 1 citation* 6. **[Beyond the Leaderboard: Rethinking Medical Benchmarks for Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-beyond-leaderboard-rethinking-medical-benchmarks/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenxuan Wang, Zizhan Ma, Guo Yu, et al.*2026 · 1 citation* 7. **[Aligning Text, Code, and Vision: A Multi-Objective Reinforcement Learning Framework for Text-to-Visualization](https://md.research.elamur.ai/free/en/papers/rahman-2026-aligning-text-code-vision-multi/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Mizanur Rahman, Mohammed Saidul Islam, Md Tahmid Rahman Laskar, et al.*2026* 8. **[Benchmark Data Contamination in Underrepresented Languages: A Comprehensive Analysis Using Brazilian Data](https://md.research.elamur.ai/free/en/papers/vilar-2026-benchmark-data-contamination-underrepresented-languages/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Iriedson Souto Maior de Moraes Vilar, David Candeia Maia, João Brunet, et al.*2026* 9. **[Charting the European LLM Benchmarking Landscape: A New Taxonomy and Registry](https://md.research.elamur.ai/free/en/papers/vintar-2026-charting-european-llm-benchmarking-landscape/) [Shaping Multilingual, Multimodal AI for the Social Sciences and Humanities @ LREC](https://md.research.elamur.ai/free/en/venues/llms4ssh/)**Spela Vintar, Mojca Brglez, Taja Kuzman Pungeršek, et al.*2026* 10. **[ExpressivityBench: Can LLMs Communicate Implicitly?](https://md.research.elamur.ai/free/en/papers/tint-2026-expressivitybench-can-llms-communicate-implicitly/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Joshua Tint, Som Sagar, Aditya Taparia, et al.*2026* 11. **[The Need for Robust and Inclusive Benchmarks in Evaluating LLMs on Arabic Text](https://md.research.elamur.ai/free/en/papers/rayes-2025-need-robust-inclusive-benchmarks-evaluating/) [International Conference on Natural Language and Speech Processing](https://md.research.elamur.ai/free/en/venues/icnlsp/)**Lubana Al Rayes, Ashraf Elnagar*2025* 30 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/laskar-2024-systematic-survey-critical-review-evaluating/) — A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and Recommendations