---
title: "Who cites G-Eval: NLG — page 3 — 1,096 citing papers"
description: "1,096 papers of the Elamur Research library cite «G-Eval: NLG Evaluation using Gpt-4 with Better Human Alignment», found in their…"
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---
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# Who cites «G-Eval: NLG Evaluation using Gpt-4 with Better Human Alignment»

1,096 papers of our library cite it (of the 149,439 whose bibliographies we read) · 243 with a page here, the most cited first · page 3 of 3 · 201–243 · [← back to «G-Eval: NLG Evaluation using Gpt-4 with Better Human Alignment»](https://md.research.elamur.ai/free/en/papers/liu-2023-g-eval-nlg-evaluation-gpt/)

[← prev](https://md.research.elamur.ai/free/en/papers/liu-2023-g-eval-nlg-evaluation-gpt/cited-by/page/2/) [1](https://md.research.elamur.ai/free/en/papers/liu-2023-g-eval-nlg-evaluation-gpt/cited-by/) [2](https://md.research.elamur.ai/free/en/papers/liu-2023-g-eval-nlg-evaluation-gpt/cited-by/page/2/) **3**

201. **[Evaluating Reference-Free Summarization Quality Metrics for Portuguese: A Study with Human Judgments in Financial News](https://md.research.elamur.ai/free/en/papers/ribeiro-2026-evaluating-reference-free-summarization-quality/) [International Conference on Computational Processing of Portuguese](https://md.research.elamur.ai/free/en/venues/propor/)**João Victor Assaoka Ribeiro, Thomas Pires Correia, José Vitor Souza Cardoso Requena, et al.*2026*
202. **[Everyone is unique: Towards Behaviorally Heterogeneous Negotiation Dialogue Systems for Debt Collection](https://md.research.elamur.ai/free/en/papers/yang-2026-everyone-is-unique-behaviorally-heterogeneous/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuhang Yang, Kai Tang, Chao Ye, et al.*2026*
203. **[FinMRAGBench: A Realistic and Complex Benchmark for Multi-Modal RAG in Financial Document Analysis](https://md.research.elamur.ai/free/en/papers/yang-2026-finmragbench-realistic-complex-benchmark-multi/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shouqing Yang, Qi Zhang, Yuhang Yang, et al.*2026*
204. **[From Questions to Assessment Tuples: A Multi-Agent Framework with Bloom-Specialized Agents and Automated Verification](https://md.research.elamur.ai/free/en/papers/wong-2026-questions-assessment-tuples-multi-agent/) [Workshop on Innovative Use of NLP for Building Educational Applications (BEA)](https://md.research.elamur.ai/free/en/venues/bea/)**Gee-Lyle Wong, Runcong Zhao, Yulan He, et al.*2026*
205. **[GlossMATE: Multi-Agent Translator Explanations for Glosses](https://md.research.elamur.ai/free/en/papers/yang-2026-glossmate-multi-agent-translator-explanations/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Changbing Yang, Patrick Littell, Gabriel Bernier-Colborne, et al.*2026*
206. **[HopWeaver: Cross-Document Synthesis of High-Quality and Authentic Multi-Hop Questions](https://md.research.elamur.ai/free/en/papers/shen-2026-hopweaver-cross-document-synthesis-high/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiyu Shen, Jiyuan Liu, Yunhe Pang, et al.*2026*
207. **[IF-GEO: Conflict-Aware Instruction Fusion for Multi-Query Generative Engine Optimization](https://md.research.elamur.ai/free/en/papers/zhou-2026-if-geo-conflict-aware-instruction/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Heyang Zhou, Jiajia Chen, Xiaolu Chen, et al.*2026*
208. **[Improving Retrieval-Augmented Generation without Taxonomy-based Error Categorization](https://md.research.elamur.ai/free/en/papers/zhang-2026-improving-retrieval-augmented-generation-without/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Gongbo Zhang, Yifan Peng, Chunhua Weng*2026*
209. **[Iterative Dual-Model Alignment for Story Evaluation](https://md.research.elamur.ai/free/en/papers/qin-2026-iterative-dual-model-alignment-story/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bruce Qin, Dan Goldwasser*2026*
210. **[Learning to Control Summaries with Score Ranking](https://md.research.elamur.ai/free/en/papers/liu-2026-learning-control-summaries-score-ranking/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hongye Liu, Liang Ding, Ricardo Henao*2026*
211. **[LLM-as-a-Jury for Machine Translation Publishability Assessment](https://md.research.elamur.ai/free/en/papers/yanishevsky-2026-llm-as-jury-machine-translation/) [Annual Conference of the European Association for Machine Translation (EAMT)](https://md.research.elamur.ai/free/en/venues/eamt/)**Alex Yanishevsky, Olivia Norris*2026*
212. [**LuxSQA: Ask Me in Luxembourgish with TTS-Augmented Spoken Question Answering arXiv:2607.02763**Nina Hosseini-Kivanani, Marco Matassoni, Alessio Brutti*2026*](https://md.research.elamur.ai/free/en/papers/hosseini-kivanani-2026-luxsqa-ask-me-luxembourgish-tts/)
213. **[Mediocrity is the key for LLM as a Judge Anchor Selection](https://md.research.elamur.ai/free/en/papers/yehiya-2026-mediocrity-is-key-llm-as/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shachar Don-Yehiya, Asaf Yehudai, Leshem Choshen, et al.*2026*
214. **[MSEarth: A Multimodal Benchmark for Earth Science Phenomenon Discovery with MLLMs](https://md.research.elamur.ai/free/en/papers/zhao-2026-msearth-multimodal-benchmark-earth-science/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiangyu Zhao, Wanghan Xu, Bo Liu, et al.*2026*
215. **[Multi-Task Reinforcement Learning for Enhanced Multimodal LLM-as-a-Judge](https://md.research.elamur.ai/free/en/papers/wu-2026-multi-task-reinforcement-learning-enhanced/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junjie Wu, Xuan Kan, Zihao He, et al.*2026*
216. **[Multimodal Claim Extraction for Fact-Checking](https://md.research.elamur.ai/free/en/papers/teo-2026-multimodal-claim-extraction-fact-checking/) [Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis](https://md.research.elamur.ai/free/en/venues/wassa/)**Joycelyn Teo, Rui Cao, Zhenyun Deng, et al.*2026*
217. **[POINTERS at UZH Shared Task 2026: Reasoning Probes for Argumentation Mining in UN Resolutions](https://md.research.elamur.ai/free/en/papers/sen-2026-pointers-uzh-shared-task-2026/) [Workshop on Argument Mining](https://md.research.elamur.ai/free/en/venues/argmining/)**Sohom Sen, Avina Nakarmi, Xun Song, et al.*2026*
218. **[Poller: Are LLMs Suitable for Evaluating Poetry Understanding Task?](https://md.research.elamur.ai/free/en/papers/wang-2026-poller-are-llms-suitable-evaluating/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shanshan Wang, Derek F. Wong, Jingming Yao, et al.*2026*
219. **[Propaganda Signals in LLMs: Perspectival Divergence and Narrative Framing in the Russia-Ukraine War](https://md.research.elamur.ai/free/en/papers/shabat-2026-propaganda-signals-llms-perspectival-divergence/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ofir Shabat, Ido Guy, Kira Radinsky*2026*
220. **[Pub-LawBench: Public-Oriented Benchmarking for LegalAI](https://md.research.elamur.ai/free/en/papers/zheng-2026-pub-lawbench-public-oriented-benchmarking/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qiaoyu Zheng, Zehan Ma, Yijing Zhang, et al.*2026*
221. **[Putting Captions to the Test: Evaluating Video Caption Quality through Multiple-Choice Question Answering](https://md.research.elamur.ai/free/en/papers/wang-2026-putting-captions-test-evaluating-video/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zizhen Wang, Bo Feng, Zhengfeng Lai, et al.*2026*
222. **[QuantumQA: Enhancing Scientific Reasoning via Physics-Consistent Dataset and Verification-Aware Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/qu-2026-quantumqa-enhancing-scientific-reasoning-physics/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Songxin Qu, Tai-Ping Sun, Yun-Jie Wang, et al.*2026*
223. **[R ESEARCH QA: Evaluating Scholarly Question Answering at Scale Across 75 Fields with Survey-Mined Questions and Rubrics](https://md.research.elamur.ai/free/en/papers/yifei-2026-r-esearch-qa-evaluating-scholarly/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Li S. Yifei, Allen Chang, Chaitanya Malaviya, et al.*2026*
224. **[RealTalk-CN: A Realistic Chinese Speech Task-Oriented Dialogue Benchmark with Cross-Modal Analysis](https://md.research.elamur.ai/free/en/papers/wang-2026-realtalk-cn-realistic-chinese-speech/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Enzhi Wang, Jiaming Zhou, Yuhang Jia, et al.*2026*
225. **[ReSQL: Self-Improving Framework for Reasoning-Aware Text-to-SQL Dataset Generation](https://md.research.elamur.ai/free/en/papers/park-2026-resql-self-improving-framework-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Minjun Park, Yongju Seong, Myoseop Sim, et al.*2026*
226. **[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*
227. **[RiT: Rubrics-in-Thinking Reinforcement Learning for Improved Reasoning in Large Language Models](https://md.research.elamur.ai/free/en/papers/tian-2026-rit-rubrics-thinking-reinforcement-learning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiaobin Tian, Shuai Yuan, Muyun Ding, et al.*2026*
228. **[SAD: A Large-Scale Strategic Argumentative Dialogue Dataset](https://md.research.elamur.ai/free/en/papers/liu-2026-sad-large-scale-strategic-argumentative/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**YongKang Liu, Jiayang Yu, Mingyang Wang, et al.*2026*
229. **[SAUCE: Summary Analysis Using Conversation Entailment](https://md.research.elamur.ai/free/en/papers/sung-2026-sauce-summary-analysis-conversation-entailment/) [Workshop on Generation, Evaluation and Metrics (GEM)](https://md.research.elamur.ai/free/en/venues/gem/)**Man-Ling Sung, Hemanth Kandula, Jeff Ma, et al.*2026*
230. **[SCURank: Ranking Multiple Candidate Summaries with Summary Content Units for Enhanced Summarization](https://md.research.elamur.ai/free/en/papers/wang-2026-scurank-ranking-multiple-candidate-summaries/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Bo-Jyun Wang, Ying-Jia Lin, Hung-Yu Kao*2026*
231. **[StealthGraph: Exposing Domain-Specific Risks in LLMs through Knowledge-Graph-Guided Harmful Prompt Generation](https://md.research.elamur.ai/free/en/papers/zheng-2026-stealthgraph-exposing-domain-specific-risks/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Huawei Zheng, Xinqi Jiang, Sen Yang, et al.*2026*
232. **[Structured Legal Document Generation in India: A Model-Agnostic Wrapper Approach with VidhikDastaavej](https://md.research.elamur.ai/free/en/papers/nigam-2026-structured-legal-document-generation-india/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Shubham Kumar Nigam, Deepak Patnaik Balaramamahanthi, Noel Shallum, et al.*2026*
233. **[Teaching Language Models to Check Grounded Claim Factuality with Human Test-Taking Strategies](https://md.research.elamur.ai/free/en/papers/ye-2026-teaching-language-models-check-grounded/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuxuan Ye, Raul Santos-Rodriguez, Edwin Simpson*2026*
234. **[TeachMaster: Generative Teaching via Code](https://md.research.elamur.ai/free/en/papers/wang-2026-teachmaster-generative-teaching-code/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuheng Wang, Runde Yang, Lin Wu, et al.*2026*
235. **[ToMELP: A Theory-of-Mind Benchmark for Route-Controlled Persuasion under the Elaboration Likelihood Model](https://md.research.elamur.ai/free/en/papers/wang-2026-tomelp-theory-mind-benchmark-route/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ruirui Wang, Haoran Zhang, Tian Lan, et al.*2026*
236. **[Too Open for Opinion? Embracing Open-Endedness in Large Language Models for Social Simulation](https://md.research.elamur.ai/free/en/papers/ma-2026-too-open-opinion-embracing-open/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Bolei Ma, Yong Cao, Indira Sen, et al.*2026*
237. **[Towards IP Intelligence: Benchmarking Large Language Models on Intellectual Property Knowledge and Practice](https://md.research.elamur.ai/free/en/papers/wang-2026-ip-intelligence-benchmarking-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qiyao Wang, Guhong Chen, Hongbo Wang, et al.*2026*
238. **[TruthTrap: A Bilingual Benchmark for Evaluating Factually Correct Yet Misleading Information in Question Answering](https://md.research.elamur.ai/free/en/papers/shafiei-2026-truthtrap-bilingual-benchmark-evaluating-factually/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mohammadamin Shafiei, Hamidreza Saffari, Mohammad Taher Pilehvar, et al.*2026*
239. **[UniDataBench: Evaluating Data Analytics Agents Across Structured and Unstructured Data](https://md.research.elamur.ai/free/en/papers/weng-2026-unidatabench-evaluating-data-analytics-agents/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Han Weng, Zhou Liu, Yuanfeng Song, et al.*2026*
240. **[Verifying the Subjective: Structured Multilingual Rewards for Low-Resource Alignment](https://md.research.elamur.ai/free/en/papers/sha-2026-verifying-subjective-structured-multilingual-rewards/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiu Sha, Mengxiao Zhu*2026*
241. **[What Makes a Good Query? Measuring the Impact of Human-Confusing Linguistic Features on LLM Performance](https://md.research.elamur.ai/free/en/papers/watson-2026-what-makes-good-query-measuring/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**William Watson, Nicole Cho, Sumitra Ganesh, et al.*2026*
242. **[When Users Are Happy but Agents Are Wrong: Multi-Dimensional Evaluation of Tool-Augmented Dialogue](https://md.research.elamur.ai/free/en/papers/shourya-2026-when-users-are-happy-but/) [Workshop on Generation, Evaluation and Metrics (GEM)](https://md.research.elamur.ai/free/en/venues/gem/)**Tanya Shourya, Yingfan Wang, Zhaoyi Joey Hou, et al.*2026*
243. **[Survey on Hallucinations in Large Language Models (大语言模型的幻觉问题研究综述)](https://md.research.elamur.ai/free/en/papers/liu-2024-hallucinations-large-language/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Zeyuan Liu (刘泽垣), Pengjiang Wang (王鹏江), Xiaobin Song (宋晓斌), et al.*2024*

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