---
title: "Who cites Fengzhe Zhou — page 2 — 566 papers of our library"
description: "566 papers of the Elamur Research library cite the works of Fengzhe Zhou, found in their bibliographies · page 2 of 2 · 101–156; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/fengzhe-zhou/cited-by/page/2/"
---
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# Who cites Fengzhe Zhou

600 citations of their works from 566 papers of our library (of the 149,439 whose bibliographies we read) · 156 with a page here, the most cited first · page 2 of 2 · 101–156 · [← Fengzhe Zhou](https://md.research.elamur.ai/free/en/authors/fengzhe-zhou/)

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

101. **[What Makes a Good Curriculum? Disentangling the Effects of Data Ordering on LLM Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/jia-2026-what-makes-good-curriculum-disentangling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yaning Jia, Chunhui Zhang, Xingjian Diao, et al.*2026 · 4 citations*
102. **[Evaluating Numeracy of Language Models as a Natural Language Inference Task](https://md.research.elamur.ai/free/en/papers/mahendra-2025-evaluating-numeracy-language-models-as/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Rahmad Mahendra, Damiano Spina, Lawrence Cavedon, et al.*2025 · 4 citations*
103. **[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*
104. **[RubricBench: Aligning Model-Generated Rubrics with Human Standards](https://md.research.elamur.ai/free/en/papers/zhou-2026-rubricbench-aligning-model-generated-rubrics/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junyi Zhou, Qiyuan Zhang, Yufei Wang, et al.*2026 · 3 citations*
105. **[ALARB: An Arabic Legal Argument Reasoning Benchmark](https://md.research.elamur.ai/free/en/papers/shairah-2025-alarb-arabic-legal-argument-reasoning/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Harethah Abu Shairah, Somayah AlHarbi, Abdulaziz AlHussein, et al.*2025 · 3 citations*
106. **[Attention Basin: Why Contextual Position Matters in Large Language Models](https://md.research.elamur.ai/free/en/papers/yi-2026-attention-basin-why-contextual-position/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zihao Yi, Zhenqing Ling, Delong Zeng, et al.*2026 · 2 citations*
107. **[LexGenius: An Expert-Level Benchmark for Large Language Models in Legal General Intelligence](https://md.research.elamur.ai/free/en/papers/liu-2026-lexgenius-expert-level-benchmark-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenjin Liu, Haoran Luo, Xin Feng, et al.*2026 · 2 citations*
108. **[OpenExempt: A Diagnostic Benchmark for Legal Reasoning and a Framework for Creating Custom Benchmarks on Demand](https://md.research.elamur.ai/free/en/papers/servantez-2026-openexempt-diagnostic-benchmark-legal-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sergio Servantez, Sarah B. Lawsky, Rajiv Jain, et al.*2026 · 2 citations*
109. **[OpenGenAlign: A Preference Dataset and Benchmark for Trustworthy Reward Modeling in Open-Ended, Long-Context Generation](https://md.research.elamur.ai/free/en/papers/zhang-2026-opengenalign-preference-dataset-benchmark-trustworthy/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hanning Zhang, Juntong Song, Juno Zhu, et al.*2026 · 2 citations*
110. **[RedOne 2.0: Rethinking Domain-specific LLM Post-Training in Social Networking Services](https://md.research.elamur.ai/free/en/papers/zhao-2026-redone-2-0-rethinking-domain/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fei zhao, Chonggang Lu, Haofu Qian, et al.*2026 · 2 citations*
111. **[Sycophants in the Courtroom: Are LLMs Fragile to Juridical Authority and Evolving Legal Standards?](https://md.research.elamur.ai/free/en/papers/molfetta-2026-sycophants-courtroom-are-llms-fragile/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lorenzo Molfetta, Alessio Cocchieri, Luca Ragazzi, et al.*2026 · 2 citations*
112. **[V-MAGE: A Game Evaluation Framework for Assessing Vision-Centric Capabilities in Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/zheng-2026-v-mage-game-evaluation-framework/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiangxi Zheng, Linjie Li, Zhengyuan Yang, et al.*2026 · 2 citations*
113. **[A Survey of Deep Learning for Geometry Problem Solving](https://md.research.elamur.ai/free/en/papers/ma-2026-survey-deep-learning-geometry-problem/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jianzhe Ma, Wenxuan Wang, Qin Jin*2026 · 1 citation*
114. **[CLASE: A Hybrid Method for Chinese Legalese Stylistic Evaluation](https://md.research.elamur.ai/free/en/papers/ma-2026-clase-hybrid-method-chinese-legalese/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Yiran Rex Ma, Yuxiao Ye, Huiyuan Xie*2026 · 1 citation*
115. **[CodeEvo: Interaction-Driven Synthesis of Code-centric Data through Hybrid and Iterative Feedback](https://md.research.elamur.ai/free/en/papers/sun-2026-codeevo-interaction-driven-synthesis-code/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qiushi Sun, Jingyang Gong, Lei Li, et al.*2026 · 1 citation*
116. **[How to Set the Learning Rate for Large-Scale Pre-training?](https://md.research.elamur.ai/free/en/papers/zhou-2026-how-set-learning-rate-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yunhua Zhou, Shuhao Xing, Junhao Huang, et al.*2026 · 1 citation*
117. **[IF-RewardBench: Benchmarking Judge Models for Instruction-Following Evaluation](https://md.research.elamur.ai/free/en/papers/wen-2026-if-rewardbench-benchmarking-judge-models/) [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*
118. **[SharVeT: Similarity-aware Parameter Sharing with Vector-based Tuning for Efficient LLM Compression](https://md.research.elamur.ai/free/en/papers/yun-2026-sharvet-similarity-aware-parameter-sharing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jeongin Yun, Jaeri Lee, Jongjin Kim, et al.*2026 · 1 citation*
119. [**GAOKAO-Eval: Does high scores truly reflect strong capabilities in LLMs? arXiv:2412.10056**Zhikai Lei, Tianyi Liang, Hanglei Hu, et al.*2024 · 1 citation*](https://md.research.elamur.ai/free/en/papers/lei-2024-gaokao-eval-high-scores/)
120. [**A Cascade Reinforcement Learning Strategy for Efficiently Enhancing the Reasoning Ability of Multimodal Large Language Models (高效提升多模态大语言模型推理能力的级联强化学习策略) Acta Automatica Sinica (自动化学报)**Weiyun Wang (王玮赟), Hengjun Pu (蒲恒骏), Linglin Jing (景凌林), et al.*2026*](https://md.research.elamur.ai/free/en/papers/wang-2026-cascade-reinforcement-learning/)
121. **[A Scalable Multi-LLM Collaboration System with Retrieval-based Selection and Exploration-Exploitation-Driven Enhancement](https://md.research.elamur.ai/free/en/papers/tang-2026-scalable-multi-llm-collaboration-system/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shengji Tang, Jianjian Cao, Weihao Lin, et al.*2026*
122. **[AgentV-RL: Scaling Reward Modeling with Agentic Verifier](https://md.research.elamur.ai/free/en/papers/zhang-2026-agentv-rl-scaling-reward-modeling/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiazheng Zhang, Ziche Fu, Zhiheng Xi, et al.*2026*
123. **[Aligning Agents via Planning: A Benchmark for Trajectory-Level Reward Modeling](https://md.research.elamur.ai/free/en/papers/wang-2026-aligning-agents-planning-benchmark-trajectory/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiaxuan Wang, Yulan Hu, Wenjin Yang, et al.*2026*
124. **[AutoTaskEval: Towards Domain-Specific and Fine-Grained Evaluation for LLMs](https://md.research.elamur.ai/free/en/papers/lyu-2026-autotaskeval-domain-specific-fine-grained/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qingqing Lyu, Linjuan Wu, Yongliang Shen, et al.*2026*
125. **[Benchmarking Temporal Reasoning and Alignment Across Chinese Dynasties](https://md.research.elamur.ai/free/en/papers/wang-2026-benchmarking-temporal-reasoning-alignment-across/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Zhenglin Wang, Jialong Wu, Pengfei Li, et al.*2026*
126. [**BenGER: Benchmarking LLM Systems on Subsumption-Based Legal Reasoning in German Law arXiv:2605.28183**Sebastian Nagl, Ann-Kristin Mayrhofer, Martin Heidebach, et al.*2026*](https://md.research.elamur.ai/free/en/papers/nagl-2026-benger-benchmarking-llm-systems-subsumption/)
127. **[Can LLMs Really Judge? A Progressive Argumentation-Mining Framework for Distinguishing Understanding from Aggregation](https://md.research.elamur.ai/free/en/papers/wang-2026-can-llms-really-judge-progressive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Fuyu Wang, Jiangtong Li, Kun Zhu, et al.*2026*
128. **[CogBench: Benchmarking Cognitive Alignment of Large Language Models in Educational Question Answering](https://md.research.elamur.ai/free/en/papers/lu-2026-cogbench-benchmarking-cognitive-alignment-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tong Lu, Zhichun Wang, Yuanhao Sun, et al.*2026*
129. **[ContextCheck: Sentence-Level Faithfulness Verification with Context-Aware Disambiguation](https://md.research.elamur.ai/free/en/papers/yin-2026-contextcheck-sentence-level-faithfulness-verification/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yueqin Yin, Yaxi Li, Xin Liu, et al.*2026*
130. **[Does RLVR Extend Reasoning Boundaries? Investigating Capability Expansion in Vision-Language Models](https://md.research.elamur.ai/free/en/papers/shen-2026-does-rlvr-extend-reasoning-boundaries/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Minghe Shen, Zhuo Zhi, Chonghan Liu, et al.*2026*
131. **[Exploring Fine-Tuning for In-Context Retrieval and Efficient KV-Caching in Long-Context Language Models](https://md.research.elamur.ai/free/en/papers/molfese-2026-exploring-fine-tuning-context-retrieval/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Francesco Maria Molfese, Momchil Hardalov, Rexhina Blloshmi, et al.*2026*
132. **[From Conversation to Evaluation: Benchmarking LLMs on Development Knowledge via SimpleDevQA](https://md.research.elamur.ai/free/en/papers/zhang-2026-conversation-evaluation-benchmarking-llms-development/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jing Zhang, Lianghong Guo, Yanlin Wang, et al.*2026*
133. **[From Query to Counsel: Structured Reasoning with a Multi-Agent Framework and Dataset for Legal Consultation](https://md.research.elamur.ai/free/en/papers/lu-2026-query-counsel-structured-reasoning-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mingfei Lu, Yi Zhang, Mengjia Wu, et al.*2026*
134. **[From Words to Pixels: A Comprehensive Survey on Large Language Models in Visual Segmentation](https://md.research.elamur.ai/free/en/papers/wang-2026-words-pixels-comprehensive-survey-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yizhou Wang, Mang Tik Chiu, Lingzhi Zhang, et al.*2026*
135. **[GenProve: Learning to Generate Text with Fine-Grained Provenance](https://md.research.elamur.ai/free/en/papers/wei-2026-genprove-learning-generate-text-fine/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingxuan Wei, Xingyue Wang, Yanghaoyu Liao, et al.*2026*
136. [**GradeLegal: Automated Grading for German Legal Cases arXiv:2605.21076**Abdullah Al Zubaer, Lorenz Wendlinger, Simon Alexander Nonn, et al.*2026*](https://md.research.elamur.ai/free/en/papers/zubaer-2026-gradelegal-automated-grading-german-legal/)
137. **[JudgeAgent: Beyond Static Benchmarks for Knowledge-Driven and Dynamic LLM Evaluation](https://md.research.elamur.ai/free/en/papers/shi-2026-judgeagent-beyond-static-benchmarks-knowledge/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhichao Shi, Xuhui Jiang, Chengjin Xu, et al.*2026*
138. **[Knowledge-to-Verification: Exploring RLVR for LLMs in Knowledge-Intensive Domains](https://md.research.elamur.ai/free/en/papers/yuan-2026-knowledge-verification-exploring-rlvr-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhonghang Yuan, Zhefan Wang, Fang Hu, et al.*2026*
139. **[Market-Bench: Benchmarking Large Language Models on Economic and Trade Competition](https://md.research.elamur.ai/free/en/papers/zheng-2026-market-bench-benchmarking-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yushuo Zheng, Huiyu Duan, Zicheng Zhang, et al.*2026*
140. **[MathSight: A Benchmark Exploring Have Vision-Language Models Really Seen in University-Level Mathematical Reasoning?](https://md.research.elamur.ai/free/en/papers/wang-2026-mathsight-benchmark-exploring-have-vision/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuandong Wang, Yao Cui, Yuxin Zhao, et al.*2026*
141. **[Memory-Driven Role-Playing: Evaluation and Enhancement of Persona Knowledge Utilization in LLMs](https://md.research.elamur.ai/free/en/papers/wang-2026-memory-driven-role-playing-evaluation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kai Wang, Haoyang You, Yang Zhang, et al.*2026*
142. **[MizanQA: A Benchmark for Multi-Answer Moroccan Legal QA](https://md.research.elamur.ai/free/en/papers/bahaj-2026-mizanqa-benchmark-multi-answer-moroccan/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Adil Bahaj, Mounir Ghogho*2026*
143. **[Parallelism and Generation Order in Masked Diffusion Language Models: Limits Today, Potential Tomorrow](https://md.research.elamur.ai/free/en/papers/zhong-2026-parallelism-generation-order-masked-diffusion/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yangyang Zhong, Yanmei Gu, Zhengqing Zang, et al.*2026*
144. **[PlanE: Meta Planning of Data, Tuning, and Inference for Extractive-based LLMs](https://md.research.elamur.ai/free/en/papers/wang-2026-plane-meta-planning-data-tuning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiacheng Wang, Weiyan Zhang, Guangya Yu*2026*
145. **[PodBench: A Comprehensive Benchmark for Instruction-Aware Audio-Oriented Podcast Script Generation](https://md.research.elamur.ai/free/en/papers/xu-2026-podbench-comprehensive-benchmark-instruction-aware/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chenning Xu, Mao Zheng, Mingyu Zheng, et al.*2026*
146. **[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*
147. **[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*
148. **[RADAR: A Reasoning-Guided Attribution Framework for Explainable Visual Data Analysis](https://md.research.elamur.ai/free/en/papers/rani-2026-radar-reasoning-guided-attribution-framework/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Anku Rani, Aparna Garimella, Apoorv Saxena, et al.*2026*
149. **[ReActR: Reasoning through Error-Activated Reflection for LLM Post-Training](https://md.research.elamur.ai/free/en/papers/sun-2026-reactr-reasoning-through-error-activated/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lina Sun*2026*
150. **[Revisiting a Pain in the Neck: A Semantic Reasoning Benchmark for Language Models](https://md.research.elamur.ai/free/en/papers/liu-2026-revisiting-pain-neck-semantic-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yang Liu, Hongming Li, Melissa Xiaohui Qin, et al.*2026*
151. **[RIPRAG: Hack a Black-box Retrieval-Augmented Generation Question-Answering System with Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/xi-2026-riprag-hack-black-box-retrieval/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Meng Xi, Sihan Lv, Yechen Jin, et al.*2026*
152. **[RouteMoA: Dynamic Routing without Pre-Inference Boosts Efficient Mixture-of-Agents](https://md.research.elamur.ai/free/en/papers/wang-2026-routemoa-dynamic-routing-without-pre/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jize Wang, Han Wu, Zhiyuan You, et al.*2026*
153. **[SDiaReward: Modeling and Benchmarking Spoken Dialogue Rewards with Modality and Colloquialness](https://md.research.elamur.ai/free/en/papers/lu-2026-sdiareward-modeling-benchmarking-spoken-dialogue/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingyu Lu, Yuhan Wang, Fan Zhuo, et al.*2026*
154. **[ViLegalLM: Language Models for Vietnamese Legal Text](https://md.research.elamur.ai/free/en/papers/nguyen-2026-vilegallm-language-models-vietnamese-legal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Truong-Phuc Nguyen, Quy-Nhan Nguyen, Minh-Tien Nguyen*2026*
155. **[WildReward: Learning Reward Models from In-the-Wild Human Interactions](https://md.research.elamur.ai/free/en/papers/peng-2026-wildreward-learning-reward-models-wild/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Peng, Yunjia Qi, Xiaozhi Wang, et al.*2026*
156. **[WildSci: Advancing Scientific Reasoning from In-the-Wild Literature](https://md.research.elamur.ai/free/en/papers/liu-2026-wildsci-advancing-scientific-reasoning-wild/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tengxiao Liu, Deepak Nathani, Zekun Li, et al.*2026*

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