---
title: "Who cites Michael Zhang — page 2 — 1,156 papers of our library"
description: "1,156 papers of the Elamur Research library cite the works of Michael Zhang, found in their bibliographies · page 2 of 2 · 101–132; the most…"
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---
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# Who cites Michael Zhang

1,166 citations of their works from 1,156 papers of our library (of the 141,840 whose bibliographies we read) · 132 with a page here, the most cited first · page 2 of 2 · 101–132 · [← Michael Zhang](https://md.research.elamur.ai/free/en/authors/michael-zhang/)

[← prev](https://md.research.elamur.ai/free/en/authors/michael-zhang/cited-by/) [1](https://md.research.elamur.ai/free/en/authors/michael-zhang/cited-by/) **2**

101. **[Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language Generation](https://md.research.elamur.ai/free/en/papers/fernandes-2023-bridging-gap-survey-integrating-human/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Patrick Fernandes, Aman Madaan, Emmy Liu, et al.*2023 · 84 citations*
102. **[DisentQA: Disentangling Parametric and Contextual Knowledge with Counterfactual Question Answering](https://md.research.elamur.ai/free/en/papers/neeman-2023-disentqa-disentangling-parametric-contextual-knowledge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ella Neeman, Roee Aharoni, Or Honovich, et al.*2023 · 84 citations*
103. **[Tree of Clarifications: Answering Ambiguous Questions with Retrieval-Augmented Large Language Models](https://md.research.elamur.ai/free/en/papers/kim-2023-tree-clarifications-answering-ambiguous-questions/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Gangwoo Kim, Sungdong Kim, Byeongguk Jeon, et al.*2023 · 82 citations*
104. [**ArtPrompt: ASCII Art-based Jailbreak Attacks against Aligned LLMs arXiv:2402.11753**Fengqing Jiang, Zhangchen Xu, Luyao Niu, et al.*2024 · 80 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2024-artprompt-ascii-art-based-jailbreak/)
105. **[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 · 75 citations*
106. **[Embarrassingly Easy Document-Level MT Metrics: How to Convert Any Pretrained Metric into a Document-Level Metric](https://md.research.elamur.ai/free/en/papers/vernikos-2022-embarrassingly-easy-document-level-mt/) [Conference on Machine Translation (WMT)](https://md.research.elamur.ai/free/en/venues/wmt/)**Giorgos Vernikos, Brian Thompson, Prashant Mathur, et al.*2022 · 68 citations*
107. **[Knowledge of Knowledge: Exploring Known-Unknowns Uncertainty with Large Language Models](https://md.research.elamur.ai/free/en/papers/amayuelas-2024-knowledge-knowledge-exploring-known-unknowns/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Alfonso Amayuelas, Kyle Wong, Liangming Pan, et al.*2024 · 66 citations*
108. [**A Comprehensive Survey on Long Context Language Modeling arXiv:2503.17407**Jiaheng Liu, Dawei Zhu, Zhiqi Bai, et al.*2025 · 64 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-comprehensive-survey-long-context-language/)
109. [**Large Language Model Routing with Benchmark Datasets arXiv:2309.15789**Tal Shnitzer, Anthony Ou, Mirian Silva, et al.*2023 · 61 citations*](https://md.research.elamur.ai/free/en/papers/shnitzer-2023-large-language-model-routing-benchmark/)
110. [**Large Language Model Agent: A Survey on Methodology, Applications and Challenges arXiv:2503.21460**Junyu Luo, Weizhi Zhang, Ye Yuan, et al.*2025 · 59 citations*](https://md.research.elamur.ai/free/en/papers/luo-2025-large-language-model-agent-survey/)
111. [**MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention arXiv:2506.13585**MiniMax, Aili Chen, Aonian Li, et al.*2025 · 58 citations*](https://md.research.elamur.ai/free/en/papers/minimax-2025-minimax-m1-scaling-test/)
112. **[DiscoScore: Evaluating Text Generation with BERT and Discourse Coherence](https://md.research.elamur.ai/free/en/papers/zhao-2023-discoscore-evaluating-text-generation-bert/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Wei Zhao, Michael Strube, Steffen Eger*2023 · 53 citations*
113. **[OG-RAG: Ontology-grounded retrieval-augmented generation for large language models](https://md.research.elamur.ai/free/en/papers/sharma-2025-og-rag-ontology-grounded-retrieval/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kartik Sharma, Peeyush Kumar, Yunqing Li*2025 · 37 citations*
114. **[Pragmatics in Language Grounding: Phenomena, Tasks, and Modeling Approaches](https://md.research.elamur.ai/free/en/papers/fried-2023-pragmatics-language-grounding-phenomena-tasks/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Daniel Fried, Nicholas Tomlin, Jennifer Hu, et al.*2023 · 36 citations*
115. **[Findings of the WMT 2020 Shared Task on Chat Translation](https://md.research.elamur.ai/free/en/papers/farajian-2020-findings-wmt-2020-shared-task/) [Conference on Machine Translation (WMT)](https://md.research.elamur.ai/free/en/venues/wmt/)**M. Amin Farajian, António V. Lopes, André F. T. Martins, et al.*2020 · 29 citations*
116. [**Taqyim: Evaluating Arabic NLP Tasks Using ChatGPT Models arXiv:2306.16322**Zaid Alyafeai, Maged S. Alshaibani, Badr AlKhamissi, et al.*2023 · 25 citations*](https://md.research.elamur.ai/free/en/papers/alyafeai-2023-taqyim-evaluating-arabic-nlp-tasks/)
117. [**DADA: Dialect Adaptation via Dynamic Aggregation of Linguistic Rules**Yanchen Liu, William Held, Diyi Yang*2023 · 20 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-dada-dialect-adaptation-dynamic-aggregation/)
118. [**Evaluating statistical language models as pragmatic reasoners arXiv:2305.01020**Benjamin Lipkin, Lionel Wong, Gabriel Grand, et al.*2023 · 18 citations*](https://md.research.elamur.ai/free/en/papers/lipkin-2023-evaluating-statistical-language-models-pragmatic/)
119. **[Bridging the Resource Gap: Exploring the Efficacy of English and Multilingual LLMs for Swedish](https://md.research.elamur.ai/free/en/papers/holmstrom-2023-bridging-resource-gap-exploring-efficacy/) [Workshop on Resources and Representations for Under-Resourced Languages and Domains](https://md.research.elamur.ai/free/en/venues/resourceful/)**Oskar Holmström, Jenny Kunz, Marco Kuhlmann*2023 · 8 citations*
120. [**MedAraBench: Large-Scale Arabic Medical Question Answering Dataset and Benchmark arXiv:2602.01714**Mouath Abu-Daoud, Leen Kharouf, Omar El Hajj, et al.*2026 · 5 citations*](https://md.research.elamur.ai/free/en/papers/abu-daoud-2026-medarabench-large-scale-arabic-medical/)
121. **[Gender Disambiguation in Machine Translation: Diagnostic Evaluation in Decoder-Only Architectures](https://md.research.elamur.ai/free/en/papers/manna-2026-gender-disambiguation-machine-translation-diagnostic/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Chiara Manna, Hosein Mohebbi, Afra Alishahi, et al.*2026 · 3 citations*
122. **[Benchmarking Large Language Models for Chinese and Japanese IMEs: Phonetic-to-Character Generation and Textual Error Correction](https://md.research.elamur.ai/free/en/papers/zou-2026-benchmarking-large-language-models-chinese/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Yuchun Zou, Tedd Lee, Xiaodi Fan, et al.*2026 · 2 citations*
123. **[Uncertainty Quantification for Evaluating Gender Bias in Machine Translation](https://md.research.elamur.ai/free/en/papers/staliunaite-2026-uncertainty-quantification-evaluating-gender-bias/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ieva Staliunaite, Julius Cheng, Andreas Vlachos*2026 · 1 citation*
124. **[A Binary Problem in Binary QA: Diverse LLMs or Diverse Question Interpretations? That Is the Ensembling Question](https://md.research.elamur.ai/free/en/papers/rosales-2026-binary-problem-binary-qa-diverse/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Rafael Rosales, Santiago Miret*2026*
125. **[AmazoniaNLP: A Survey of Extreme Low-Resource Languages in the Peruvian-Brazilian Amazon](https://md.research.elamur.ai/free/en/papers/zevallos-2026-amazonianlp-survey-extreme-low-resource/) [SIGUL Joint Workshop with ELE, EURALI, and DCLRL: Towards Inclusivity and Equality: Language Resources and Technologies for Under-Resourced and Endangered Languages](https://md.research.elamur.ai/free/en/venues/sigul/)**Rodolfo Joel Zevallos, Fabrício Carraro, John E. Ortega*2026*
126. **[How Far Can Bias Go? Tracing Bias from Pre-Training Data to Alignment](https://md.research.elamur.ai/free/en/papers/thaler-2026-how-far-can-bias-go/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Marion Thaler, Abdullatif Köksal, Alina Leidinger, et al.*2026*
127. **[Is Biomedical Specialization Still Worth It? Insights from Domain-Adaptive Language Modelling with a New French Health Corpus](https://md.research.elamur.ai/free/en/papers/mannion-2026-is-biomedical-specialization-still-worth/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Aidan Mannion, Cécile Macaire, Armand Violle, et al.*2026*
128. [**Sentiment Classification of Gaza War Headlines: A Comparative Analysis of Large Language Models and Arabic Fine-Tuned BERT Models arXiv:2604.08566 · SSRN (2026)**Amr Eleraqi; Hager H. Mustafa;, Abdul Hadi N. Ahmed*2026*](https://md.research.elamur.ai/free/en/papers/eleraqi-2026-sentiment-classification-gaza-war-headlines/)
129. **[The MaTOS Pipeline for the Translation of Scientific Abstracts on the HAL Platform](https://md.research.elamur.ai/free/en/papers/tsolakis-2026-matos-pipeline-translation-scientific-abstracts/) [Annual Conference of the European Association for Machine Translation (EAMT)](https://md.research.elamur.ai/free/en/venues/eamt/)**Panagiotis Tsolakis, Ziqian Peng, Laurent Romary, et al.*2026*
130. [**Embodied Intelligence Systems Based on Large Models: A Survey (基于大模型的具身智能系统综述) Acta Automatica Sinica (自动化学报)**Wensheng Wang (王文晟), Ning Tan (谭宁), Kai Huang (黄凯), et al.*2025*](https://md.research.elamur.ai/free/en/papers/wang-2025-embodied-intelligence-systems/)
131. **[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*
132. [**Questions After ChatGPT: Opportunities and Challenges of Very Large Pre-trained Models (问答ChatGPT之后: 超大预训练模型的机遇和挑战) Acta Automatica Sinica (自动化学报)**Jingwei Lu (卢经纬), Chao Guo (郭超), Xingyuan Dai (戴星原), et al.*2023*](https://md.research.elamur.ai/free/en/papers/lu-2023-questions-after-chatgpt/)

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