---
title: "Who cites Seongyun Lee — 106 papers of our library"
description: "106 papers of the Elamur Research library cite the works of Seongyun Lee, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/seongyun-lee/cited-by/"
---
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# Who cites Seongyun Lee

107 citations of their works from 106 papers of our library (of the 149,439 whose bibliographies we read) · 44 with a page here, the most cited first · [← Seongyun Lee](https://md.research.elamur.ai/free/en/authors/seongyun-lee/)

1. [**Prometheus 2: An Open Source Language Model Specialized in Evaluating Other Language Models arXiv:2405.01535**Seungone Kim, Juyoung Suk, Shayne Longpre, et al.*2024 · 234 citations*](https://md.research.elamur.ai/free/en/papers/kim-2024-prometheus-2-open-source-language/)
2. **[LLM-based NLG Evaluation: Current Status and Challenges](https://md.research.elamur.ai/free/en/papers/gao-2025-llm-based-nlg-evaluation-current/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Mingqi Gao, Xinyu Hu, Xunjian Yin, et al.*2025 · 153 citations*
3. [**To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning arXiv:2409.12183**Zayne Sprague, Fangcong Yin, Juan Diego Rodriguez, et al.*2024 · 138 citations*](https://md.research.elamur.ai/free/en/papers/sprague-2024-cot-cot-chain-thought-helps/)
4. [**JudgeBench: A Benchmark for Evaluating LLM-based Judges arXiv:2410.12784**Sijun Tan, Siyuan Zhuang, Kyle Montgomery, et al.*2024 · 101 citations*](https://md.research.elamur.ai/free/en/papers/tan-2024-judgebench-benchmark-evaluating-llm-based/)
5. [**OpenScholar: Synthesizing Scientific Literature with Retrieval-augmented LMs arXiv:2411.14199**Akari Asai, Jacqueline He, Rulin Shao, et al.*2024 · 62 citations*](https://md.research.elamur.ai/free/en/papers/asai-2024-openscholar-synthesizing-scientific-literature/)
6. **[Small Models Struggle to Learn from Strong Reasoners](https://md.research.elamur.ai/free/en/papers/li-2025-small-models-struggle-learn-strong/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuetai Li, Xiang Yue, Zhangchen Xu, et al.*2025 · 61 citations*
7. **[AssistantBench: Can Web Agents Solve Realistic and Time-Consuming Tasks?](https://md.research.elamur.ai/free/en/papers/yoran-2024-assistantbench-can-web-agents-solve/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ori Yoran, Samuel Joseph Amouyal, Chaitanya Malaviya, et al.*2024 · 46 citations*
8. [**Pangea: A Fully Open Multilingual Multimodal LLM for 39 Languages arXiv:2410.16153**Xiang Yue, Yueqi Song, Akari Asai, et al.*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/yue-2024-pangea-fully-open-multilingual-multimodal/)
9. [**A Survey of Frontiers in LLM Reasoning: Inference Scaling, Learning to Reason, and Agentic Systems arXiv:2504.09037**Zixuan Ke, Fangkai Jiao, Yifei Ming, et al.*2025 · 39 citations*](https://md.research.elamur.ai/free/en/papers/ke-2025-survey-frontiers-llm-reasoning-inference/)
10. **[Direct Judgement Preference Optimization](https://md.research.elamur.ai/free/en/papers/wang-2025-direct-judgement-preference-optimization/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**PeiFeng Wang, Austin Xu, Yilun Zhou, et al.*2025 · 35 citations*
11. **[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*
12. [**SciReplicate-Bench: Benchmarking LLMs in Agent-driven Algorithmic Reproduction from Research Papers arXiv:2504.00255**Yanzheng Xiang, Hanqi Yan, Shuyin Ouyang, et al.*2025 · 23 citations*](https://md.research.elamur.ai/free/en/papers/xiang-2025-scireplicate-bench-benchmarking-llms/)
13. **[MLR-Bench: Evaluating AI Agents on Open-Ended Machine Learning Research](https://md.research.elamur.ai/free/en/papers/chen-2025-mlr-bench-evaluating-ai/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Hui Chen, Miao Xiong, Yujie Lu, et al.*2025 · 21 citations*
14. **[Measuring Chain of Thought Faithfulness by Unlearning Reasoning Steps](https://md.research.elamur.ai/free/en/papers/tutek-2025-measuring-chain-thought-faithfulness-unlearning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Martin Tutek, Fateme Hashemi Chaleshtori, Ana Marasovic, et al.*2025 · 15 citations*
15. **[Find Your Optimal Teacher: Personalized Data Synthesis via Router-Guided Multi-Teacher Distillation](https://md.research.elamur.ai/free/en/papers/zhang-2026-find-your-optimal-teacher-personalized/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hengyuan Zhang, Shiping Yang, Xiao Liang, et al.*2026 · 13 citations*
16. [**When AI Co-Scientists Fail: SPOT-a Benchmark for Automated Verification of Scientific Research arXiv:2505.11855**Guijin Son, Jiwoo Hong, Honglu Fan, et al.*2025 · 13 citations*](https://md.research.elamur.ai/free/en/papers/son-2025-ai-co-scientists-fail/)
17. [**From Calculation to Adjudication: Examining LLM judges on Mathematical Reasoning Tasks arXiv:2409.04168**Andreas Stephan, Dawei Zhu, Matthias Aßenmacher, et al.*2024 · 13 citations*](https://md.research.elamur.ai/free/en/papers/stephan-2024-calculation-adjudication-examining-llm-judges/)
18. [**AI Scientists Fail Without Strong Implementation Capability arXiv:2506.01372**Minjun Zhu, Qiujie Xie, Yixuan Weng, et al.*2025 · 12 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-ai-scientists-fail-strong/)
19. **[AutoReproduce: Automatic AI Experiment Reproduction with Paper Lineage](https://md.research.elamur.ai/free/en/papers/zhao-2025-autoreproduce-automatic-ai-experiment/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xuanle Zhao, Zilin Sang, Yuxuan Li, et al.*2025 · 12 citations*
20. [**TRAIL: Trace Reasoning and Agentic Issue Localization arXiv:2505.08638**Darshan Deshpande, Varun Gangal, Hersh Mehta, et al.*2025 · 12 citations*](https://md.research.elamur.ai/free/en/papers/deshpande-2025-trail-trace-reasoning-agentic-issue/)
21. **[Cross-Lingual Auto Evaluation for Assessing Multilingual LLMs](https://md.research.elamur.ai/free/en/papers/doddapaneni-2025-cross-lingual-auto-evaluation-assessing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sumanth Doddapaneni, Mohammed Safi Ur Rahman Khan, Dilip Venkatesh, et al.*2025 · 11 citations*
22. **[An Empirical Study of LLM-as-a-Judge: How Design Choices Impact Evaluation Reliability](https://md.research.elamur.ai/free/en/papers/yamauchi-2026-empirical-study-llm-as-judge/) [Workshop on Generation, Evaluation and Metrics (GEM)](https://md.research.elamur.ai/free/en/venues/gem/)**Yusuke Yamauchi, Taro Yano, Masafumi Oyamada*2026 · 10 citations*
23. [**Rethinking Rubric Generation for Improving LLM Judge and Reward Modeling for Open-ended Tasks arXiv:2602.05125**William F. Shen, Xinchi Qiu, Chenxi Whitehouse, et al.*2026 · 9 citations*](https://md.research.elamur.ai/free/en/papers/shen-2026-rethinking-rubric-generation-improving-llm/)
24. [**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/)
25. [**mR3: Multilingual Rubric-Agnostic Reward Reasoning Models arXiv:2510.01146**David Anugraha, Shou-Yi Hung, Zilu Tang, et al.*2025 · 5 citations*](https://md.research.elamur.ai/free/en/papers/anugraha-2025-mr3-multilingual-rubric-agnostic-reward/)
26. **[The Automated LLM Speedrunning Benchmark: Reproducing NanoGPT Improvements](https://md.research.elamur.ai/free/en/papers/zhao-2025-automated-llm-speedrunning-benchmark/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Bingchen Zhao, Despoina Magka, Minqi Jiang, et al.*2025 · 4 citations*
27. **[J4R: Learning to Judge with Equivalent Initial State Group Relative Policy Optimization](https://md.research.elamur.ai/free/en/papers/xu-2026-j4r-learning-judge-equivalent-initial/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Austin Xu, Yilun Zhou, Xuan-Phi Nguyen, et al.*2026 · 3 citations*
28. **[Korean Canonical Legal Benchmark: Toward Knowledge-Independent Evaluation of LLMs' Legal Reasoning Capabilities](https://md.research.elamur.ai/free/en/papers/oh-2026-korean-canonical-legal-benchmark-knowledge/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Hongseok Oh, Wonseok Hwang, Kyoung-Woon On*2026 · 3 citations*
29. **[Graders Should Cheat: Privileged Information Enables Expert-Level Automated Evaluations](https://md.research.elamur.ai/free/en/papers/zhou-2025-graders-should-cheat-privileged-information/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jin Peng Zhou, Séb Arnold, Nan Ding, et al.*2025 · 3 citations*
30. [**Training AI Scientists to Replicate Research arXiv:2608.13331**Damon Falck, Samer Sabri, Anja Surina, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/falck-2026-training-ai-scientists-replicate/)
31. **[Decentralized Arena: Towards Democratic and Scalable Automatic Evaluation of Language Models](https://md.research.elamur.ai/free/en/papers/yin-2026-decentralized-arena-democratic-scalable-automatic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yanbin Yin, Kun Zhou, Zhen Wang, et al.*2026 · 1 citation*
32. **[DRAGON: Domain-specific Robust Automatic Data Generation for RAG Optimization](https://md.research.elamur.ai/free/en/papers/shen-2026-dragon-domain-specific-robust-automatic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haiyang Shen, Hang Yan, Zhongshi Xing, et al.*2026 · 1 citation*
33. **[InferenceDynamics: Adaptive LLM Routing through Structured Capability and Knowledge Profiling](https://md.research.elamur.ai/free/en/papers/shi-2026-inferencedynamics-adaptive-llm-routing-through/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haochen Shi, Tianshi Zheng, Weiqi Wang, et al.*2026 · 1 citation*
34. **[RECAP: REwriting Conversations for Intent Understanding in Agentic Planning](https://md.research.elamur.ai/free/en/papers/mitra-2026-recap-rewriting-conversations-intent-understanding/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kushan Mitra, Dan Zhang, Hannah Kim, et al.*2026 · 1 citation*
35. **[SCAN: Structured Capability Assessment and Navigation for LLMs](https://md.research.elamur.ai/free/en/papers/wang-2026-scan-structured-capability-assessment-navigation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zongqi Wang, Tianle Gu, Chen Gong, et al.*2026 · 1 citation*
36. **[Synthetic Doctor-Patient Dialogue Generation for Robust Medical ASR: A Scalable Pipeline for Vocabulary Expansion and Privacy Preservation](https://md.research.elamur.ai/free/en/papers/liu-2026-synthetic-doctor-patient-dialogue-generation/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Kefei Liu, Meizhu Liu*2026 · 1 citation*
37. **[Bi-Text Mining across German Dialects: On the Role of Synthetic Training Data for Dialect Adaptation](https://md.research.elamur.ai/free/en/papers/wang-2026-bi-text-mining-across-german/) [Workshop on Building and Using Comparable Corpora (BUCC)](https://md.research.elamur.ai/free/en/venues/bucc/)**Jing Wang, Barbara Plank, Robert Litschko*2026*
38. [**Computational models of pragmatic reasoning with flexible generation of meaning and expression alternatives arXiv:2607.18443**Polina Tsvilodub, Fausto Carcassi, Michael Franke*2026*](https://md.research.elamur.ai/free/en/papers/tsvilodub-2026-computational-models-pragmatic-reasoning-flexible/)
39. **[ExStrucTiny: A Benchmark for Schema-Variable Structured Information Extraction from Document Images](https://md.research.elamur.ai/free/en/papers/sibue-2026-exstructiny-benchmark-schema-variable-structured/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Mathieu Sibue, Andrés Muñoz Garza, Samuel Mensah, et al.*2026*
40. **[MMSciCode: Real-world Evaluation of Multilingual Multi-Discipline Scientific Research Coding](https://md.research.elamur.ai/free/en/papers/xia-2026-mmscicode-real-world-evaluation-multilingual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xue Xia, Zheyuan Yang, Arman Cohan, et al.*2026*
41. **[MMTutorBench: The First Multimodal Benchmark for AI Math Tutoring](https://md.research.elamur.ai/free/en/papers/yang-2026-mmtutorbench-first-multimodal-benchmark-ai/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tengchao Yang, Sichen Guo, Mengzhao Jia, et al.*2026*
42. **[TextMineX: Data, Evaluation Framework and Ontology-guided LLM Pipeline for Humanitarian Mine Action](https://md.research.elamur.ai/free/en/papers/zhou-2026-textminex-data-evaluation-framework-ontology/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chenyue Zhou, Gürkan Solmaz, Flavio Cirillo, et al.*2026*
43. **[What Makes AI Research Replicable? Executable Knowledge Graphs as Scientific Knowledge Representations](https://md.research.elamur.ai/free/en/papers/luo-2026-what-makes-ai-research-replicable/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yujie Luo, Zhuoyun Yu, Xuehai Wang, et al.*2026*
44. [**Classifying German Language Proficiency Levels Using Large Language Models arXiv:2512.06483**Elias-Leander Ahlers; Witold Brunsmann;, Malte Schilling*2025*](https://md.research.elamur.ai/free/en/papers/ahlers-2025-classifying-german-language-proficiency-levels/)

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

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