---
title: "Who cites Juyoung Suk — 281 papers of our library"
description: "281 papers of the Elamur Research library cite the works of Juyoung Suk, found in their bibliographies; the most cited first."
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---
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# Who cites Juyoung Suk

307 citations of their works from 281 papers of our library (of the 149,439 whose bibliographies we read) · 81 with a page here, the most cited first · [← Juyoung Suk](https://md.research.elamur.ai/free/en/authors/juyoung-suk/)

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. [**LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods arXiv:2412.05579**Haitao Li, Qian Dong, Junjie Chen, et al.*2024 · 195 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llms-judges-comprehensive-survey-llm/)
3. **[Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-towards-reasoning-era-survey-long/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Libo Qin, Jinhao Liu, et al.*2025 · 176 citations*
4. **[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*
5. **[Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-Experts](https://md.research.elamur.ai/free/en/papers/wang-2024-interpretable-preferences-multi-objective-reward/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haoxiang Wang, Wei Xiong, Tengyang Xie, et al.*2024 · 153 citations*
6. [**LLMs instead of Human Judges? A Large Scale Empirical Study across 20 NLP Evaluation Tasks arXiv:2406.18403**Anna Bavaresco, Raffaella Bernardi, Leonardo Bertolazzi, et al.*2024 · 141 citations*](https://md.research.elamur.ai/free/en/papers/bavaresco-2024-llms-instead-human-judges-large/)
7. [**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/)
8. **[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/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Md Tahmid Rahman Laskar, Sawsan Alqahtani, M Saiful Bari, et al.*2024 · 105 citations*
9. [**Arcee's MergeKit: A Toolkit for Merging Large Language Models arXiv:2403.13257**Charles Goddard, Shamane Siriwardhana, Malikeh Ehghaghi, et al.*2024 · 105 citations*](https://md.research.elamur.ai/free/en/papers/goddard-2024-arcee-s-mergekit-toolkit-merging/)
10. [**WildBench: Benchmarking LLMs with Challenging Tasks from Real Users in the Wild arXiv:2406.04770**Bill Yuchen Lin, Yuntian Deng, Khyathi Chandu, et al.*2024 · 105 citations*](https://md.research.elamur.ai/free/en/papers/lin-2024-wildbench-benchmarking-llms-challenging-tasks/)
11. [**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/)
12. [**HelpSteer2: Open-source dataset for training top-performing reward models arXiv:2406.08673**Zhilin Wang, Yi Dong, Olivier Delalleau, et al.*2024 · 82 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-helpsteer2-open-source-dataset-training/)
13. **[AudioBench: A Universal Benchmark for Audio Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2025-audiobench-universal-benchmark-audio-large/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Bin Wang, Xunlong Zou, Geyu Lin, et al.*2025 · 77 citations*
14. [**Rubrics as Rewards: Reinforcement Learning Beyond Verifiable Domains arXiv:2507.17746**Anisha Gunjal, Anthony Wang, Elaine Lau, et al.*2025 · 73 citations*](https://md.research.elamur.ai/free/en/papers/gunjal-2025-rubrics-rewards-reinforcement-learning-verifiable/)
15. **[OffsetBias: Leveraging Debiased Data for Tuning Evaluators](https://md.research.elamur.ai/free/en/papers/park-2024-offsetbias-leveraging-debiased-data-tuning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Junsoo Park, Seungyeon Jwa, Ren Meiying, et al.*2024 · 67 citations*
16. [**Inference-Time Scaling for Generalist Reward Modeling arXiv:2504.02495**Zijun Liu, Peiyi Wang, Runxin Xu, et al.*2025 · 65 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-inference-time-scaling-generalist/)
17. **[Meta-Rewarding Language Models: Self-Improving Alignment with LLM-as-a-Meta-Judge](https://md.research.elamur.ai/free/en/papers/wu-2025-meta-rewarding-language-models-self/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tianhao Wu, Weizhe Yuan, Olga Golovneva, et al.*2025 · 64 citations*
18. [**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/)
19. **[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*
20. **[Unifying AI Tutor Evaluation: An Evaluation Taxonomy for Pedagogical Ability Assessment of LLM-Powered AI Tutors](https://md.research.elamur.ai/free/en/papers/maurya-2025-unifying-ai-tutor-evaluation-evaluation/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Kaushal Kumar Maurya, Kv Aditya Srivatsa, Kseniia Petukhova, et al.*2025 · 53 citations*
21. **[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*
22. **[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*
23. **[Evaluating Language Models as Synthetic Data Generators](https://md.research.elamur.ai/free/en/papers/kim-2025-evaluating-language-models-as-synthetic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Seungone Kim, Juyoung Suk, Xiang Yue, et al.*2025 · 32 citations*
24. **[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*
25. [**LLM-as-a-Judge & Reward Model: What They Can and Cannot Do arXiv:2409.11239**Guijin Son, Hyunwoo Ko, Hoyoung Lee, et al.*2024 · 27 citations*](https://md.research.elamur.ai/free/en/papers/son-2024-llm-judge-reward-model-they/)
26. **[IberoBench: A Benchmark for LLM Evaluation in Iberian Languages](https://md.research.elamur.ai/free/en/papers/baucells-2025-iberobench-benchmark-llm-evaluation-iberian/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Irene Baucells, Javier Aula-Blasco, Iria de-Dios-Flores, et al.*2025 · 24 citations*
27. **[Evaluating the Consistency of LLM Evaluators](https://md.research.elamur.ai/free/en/papers/lee-2025-evaluating-consistency-llm-evaluators/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Noah Lee, Jiwoo Hong, James Thorne*2025 · 16 citations*
28. **[CalibraEval: Calibrating Prediction Distribution to Mitigate Selection Bias in LLMs-as-Judges](https://md.research.elamur.ai/free/en/papers/li-2025-calibraeval-calibrating-prediction-distribution-mitigate/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haitao Li, Junjie Chen, Qingyao Ai, et al.*2025 · 15 citations*
29. **[Improve LLM-as-a-Judge Ability as a General Ability](https://md.research.elamur.ai/free/en/papers/yu-2025-improve-llm-as-judge-ability/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jiachen Yu, Shaoning Sun, Xiaohui Hu, et al.*2025 · 15 citations*
30. **[Does Context Matter? ContextualJudgeBench for Evaluating LLM-based Judges in Contextual Settings](https://md.research.elamur.ai/free/en/papers/xu-2025-does-context-matter-contextualjudgebench-evaluating/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Austin Xu, Srijan Bansal, Yifei Ming, et al.*2025 · 14 citations*
31. **[OmniThink: Expanding Knowledge Boundaries in Machine Writing through Thinking](https://md.research.elamur.ai/free/en/papers/xi-2025-omnithink-expanding-knowledge-boundaries-machine/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zekun Xi, Wenbiao Yin, Jizhan Fang, et al.*2025 · 14 citations*
32. **[CodeJudgeBench: Benchmarking LLM-as-a-Judge for Coding Tasks](https://md.research.elamur.ai/free/en/papers/jiang-2026-codejudgebench-benchmarking-llm-as-judge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hongchao Jiang, Yiming Chen, Yushi Cao, et al.*2026 · 13 citations*
33. **[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*
34. [**Evaluating LLMs' Divergent Thinking Capabilities for Scientific Idea Generation with Minimal Context arXiv:2412.17596**Kai Ruan, Xuan Wang, Jixiang Hong, et al.*2024 · 13 citations*](https://md.research.elamur.ai/free/en/papers/ruan-2024-evaluating-llms-divergent-thinking-capabilities/)
35. [**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/)
36. **[Whose Boat Does it Float? Improving Personalization in Preference Tuning via Inferred User Personas](https://md.research.elamur.ai/free/en/papers/balepur-2025-whose-boat-does-it-float/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nishant Balepur, Vishakh Padmakumar, Fumeng Yang, et al.*2025 · 12 citations*
37. **[MORQA: Benchmarking Evaluation Metrics for Medical Open-Ended Question Answering](https://md.research.elamur.ai/free/en/papers/yim-2026-morqa-benchmarking-evaluation-metrics-medical/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Wen-wai Yim, Asma Ben Abacha, Zixuan Yu, et al.*2026 · 11 citations*
38. **[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*
39. **[Influences on LLM Calibration: A Study of Response Agreement, Loss Functions, and Prompt Styles](https://md.research.elamur.ai/free/en/papers/xia-2025-influences-llm-calibration-study-response/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuxi Xia, Pedro Henrique Luz De Araujo, Klim Zaporojets, et al.*2025 · 11 citations*
40. **[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*
41. **[Reason Only When Needed: Efficient Generative Reward Modeling via Model-Internal Uncertainty](https://md.research.elamur.ai/free/en/papers/xue-2026-reason-only-when-needed-efficient/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chao Xue, Yao Wang, Mengqiao Liu, et al.*2026 · 8 citations*
42. **[Beyond Outlining: Heterogeneous Recursive Planning for Adaptive Long-form Writing with Language Models](https://md.research.elamur.ai/free/en/papers/xiong-2025-beyond-outlining-heterogeneous-recursive-planning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ruibin Xiong, Yimeng Chen, Dmitrii Khizbullin, et al.*2025 · 8 citations*
43. **[SciRAG: Adaptive, Citation-Aware, and Outline-Guided Retrieval and Synthesis for Scientific Literature](https://md.research.elamur.ai/free/en/papers/ding-2026-scirag-adaptive-citation-aware-outline/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Hang Ding, Yilun Zhao, Tiansheng Hu, et al.*2026 · 7 citations*
44. **[When Life Gives You Samples: The Benefits of Scaling up Inference Compute for Multilingual LLMs](https://md.research.elamur.ai/free/en/papers/khairi-2025-when-life-gives-you-samples/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ammar Khairi, Daniel D'souza, Ye Shen, et al.*2025 · 6 citations*
45. **[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*
46. [**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/)
47. **[Multi-Session Client-Centered Treatment Outcome Evaluation in Psychotherapy](https://md.research.elamur.ai/free/en/papers/na-2026-multi-session-client-centered-treatment/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Hongbin Na, Tao Shen, Shumao Yu, et al.*2026 · 4 citations*
48. **[DARS: Dynamic Action Re-Sampling to Enhance Coding Agent Performance by Adaptive Tree Traversal](https://md.research.elamur.ai/free/en/papers/aggarwal-2025-dars-dynamic-action-re-sampling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Vaibhav Aggarwal, Ojasv Kamal, Abhinav Japesh, et al.*2025 · 4 citations*
49. **[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*
50. **[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*
51. **[MedQA-CS: Objective Structured Clinical Examination (OSCE)-Style Benchmark for Evaluating LLM Clinical Skills](https://md.research.elamur.ai/free/en/papers/yao-2026-medqa-cs-objective-structured-clinical/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Zonghai Yao, Zihao Zhang, Chaolong Tang, et al.*2026 · 3 citations*
52. **[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*
53. **[AITutor-EvalKit: Exploring the Capabilities of AI Tutors](https://md.research.elamur.ai/free/en/papers/naeem-2026-aitutor-evalkit-exploring-capabilities-ai/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Numaan Naeem, Kaushal Kumar Maurya, Kseniia Petukhova, et al.*2026 · 2 citations*
54. [**Benchmarking Frontier LLMs on Arabic Cultural and Sociolinguistic Knowledge: A Cross-Evaluation Framework with Human SME Ground Truth arXiv:2607.00139**Sajjad Abdoli, Ghassan Al-Sumaidaee, Ahmad ElShiekh, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/abdoli-2026-benchmarking-frontier-llms-arabic-cultural/)
55. **[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*
56. **[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*
57. **[IF-CRITIC: Towards a Fine-Grained LLM Critic for Instruction-Following Evaluation](https://md.research.elamur.ai/free/en/papers/wen-2026-if-critic-fine-grained-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bosi Wen, Yilin Niu, Cunxiang Wang, et al.*2026 · 1 citation*
58. **[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*
59. **[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*
60. **[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*
61. **[SEFL: A Framework for Generating Synthetic Educational Assignment Feedback with LLM Agents](https://md.research.elamur.ai/free/en/papers/zhang-2026-sefl-framework-generating-synthetic-educational/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Mike Zhang, Amalie Pernille Dilling, Léon Gondelman, et al.*2026 · 1 citation*
62. **[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*
63. **[A Virtual Assistant for Architectural Design in a VR Environment](https://md.research.elamur.ai/free/en/papers/salaberria-2026-virtual-assistant-architectural-design-vr/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Ander Salaberria, Oier Ijurco, Markel Ferro, et al.*2026*
64. **[Alignment Tuning for Large Language Models: A Data-Centric Lens on Alignment Data Pipelines](https://md.research.elamur.ai/free/en/papers/song-2026-alignment-tuning-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hwanjun Song*2026*
65. **[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*
66. **[Calibrating LLM Judges: Linear Probes for Fast and Reliable Uncertainty Estimation](https://md.research.elamur.ai/free/en/papers/radharapu-2026-calibrating-llm-judges-linear-probes/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bhaktipriya Radharapu, Eshika Saxena, Kenneth Li, et al.*2026*
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