--- title: "Who cites Leveraging Large Language — 40 citing papers" description: "40 papers of the Elamur Research library cite «Leveraging Large Language Models for NLG Evaluation: Advances and Challenges», found in their…" canonical: "https://research.elamur.ai/free/en/papers/li-2024-leveraging-large-language-models-nlg/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/li-2024-leveraging-large-language-models-nlg/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Leveraging Large Language Models for NLG…](https://md.research.elamur.ai/free/en/papers/li-2024-leveraging-large-language-models-nlg/) / cited by # Who cites «Leveraging Large Language Models for NLG Evaluation: Advances and Challenges» 40 papers of our library cite it (of the 149,439 whose bibliographies we read) · 10 with a page here, the most cited first · [← back to «Leveraging Large Language Models for NLG Evaluation: Advances and Challenges»](https://md.research.elamur.ai/free/en/papers/li-2024-leveraging-large-language-models-nlg/) 1. [**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/) 2. **[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* 3. **[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* 4. **[EvolvR: Self-Evolving Pairwise Reasoning for Story Evaluation to Enhance Generation](https://md.research.elamur.ai/free/en/papers/wang-2026-evolvr-self-evolving-pairwise-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinda Wang, Zhengxu Hou, Yangshijie Zhang, et al.*2026 · 1 citation* 5. **[SynthLLM: An LLM-based Scalable Synthetic Data Generation Pipeline for Low-Resource Languages](https://md.research.elamur.ai/free/en/papers/panahi-2026-synthllm-llm-based-scalable-synthetic/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Solmaz Panahi, Vasudevan Nedumpozhimana, John Kelleher*2026 · 1 citation* 6. **[When LLMs Annotate: Reliability Challenges in Low-Resource NLI](https://md.research.elamur.ai/free/en/papers/panahi-2026-when-llms-annotate-reliability-challenges/) [Workshop on Language Models for Low-Resource Languages](https://md.research.elamur.ai/free/en/venues/loreslm/)**Solmaz Panahi, John Kelleher, Vasudevan Nedumpozhimana*2026 · 1 citation* 7. **[ChangJuan: A Comprehensive Benchmark for Book-Length Chinese Story Evaluation](https://md.research.elamur.ai/free/en/papers/yang-2026-changjuan-comprehensive-benchmark-book-length/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Dingyi Yang, Mingshuo Wang, Qin Jin*2026* 8. **[DefGen-Bench: A Benchmark for Chinese Criminal Defence Opinion Generation in LegalAI](https://md.research.elamur.ai/free/en/papers/zhang-2026-defgen-bench-benchmark-chinese-criminal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Senbo Zhang, Qiqi Wang, Fanghao Lou, et al.*2026* 9. **[LegalChainReasoner: Grounding Criminal Judicial Opinion Generation via Structured Legal Chains](https://md.research.elamur.ai/free/en/papers/shi-2026-legalchainreasoner-grounding-criminal-judicial-opinion/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weizhe Shi, Qiqi Wang, Yihong Pan, et al.*2026* 10. **[Reward Modeling for Scientific Writing Evaluation](https://md.research.elamur.ai/free/en/papers/sahinuc-2026-reward-modeling-scientific-writing-evaluation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Furkan Şahinuç, Subhabrata Dutta, Iryna Gurevych*2026* 30 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/li-2024-leveraging-large-language-models-nlg/) — Leveraging Large Language Models for NLG Evaluation: Advances and Challenges