---
title: "Who cites Yunbo Cao — page 2 — 546 papers of our library"
description: "546 papers of the Elamur Research library cite the works of Yunbo Cao, found in their bibliographies · page 2 of 2 · 101–137; the most cited first."
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---
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# Who cites Yunbo Cao

549 citations of their works from 546 papers of our library (of the 149,439 whose bibliographies we read) · 137 with a page here, the most cited first · page 2 of 2 · 101–137 · [← Yunbo Cao](https://md.research.elamur.ai/free/en/authors/yunbo-cao/)

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

101. **[Beyond Literal Mapping: Benchmarking and Improving Non-Literal Translation Evaluation](https://md.research.elamur.ai/free/en/papers/tian-2026-beyond-literal-mapping-benchmarking-improving/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yanzhi Tian, Cunxiang Wang, Zeming Liu, et al.*2026 · 5 citations*
102. **[Learning to Judge: LLMs Designing and Applying Evaluation Rubrics](https://md.research.elamur.ai/free/en/papers/siro-2026-learning-judge-llms-designing-applying/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Clemencia Siro, Pourya Aliannejadi, Mohammad Aliannejadi*2026 · 5 citations*
103. **[Add-One-In: Incremental Sample Selection for Large Language Models via a Choice-Based Greedy Paradigm](https://md.research.elamur.ai/free/en/papers/li-2025-add-one-incremental-sample-selection/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhuo Li, Yuhao Du, Xiaoqi Jiao, et al.*2025 · 5 citations*
104. **[EIFBENCH: Extremely Complex Instruction Following Benchmark for Large Language Models](https://md.research.elamur.ai/free/en/papers/zou-2025-eifbench-extremely-complex-instruction-following/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tao Zou, Xinghua Zhang, Haiyang Yu, et al.*2025 · 5 citations*
105. **[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*
106. **[How Long Reasoning Chains Influence LLMs' Judgment of Answer Factuality](https://md.research.elamur.ai/free/en/papers/tu-2026-how-long-reasoning-chains-influence/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Minzhu Tu, Shiyu Ni, Keping Bi*2026 · 3 citations*
107. **[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*
108. **[ClozEx: A Task toward Generation of English Cloze Explanation](https://md.research.elamur.ai/free/en/papers/zhang-2023-clozex-task-generation-english-cloze/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zizheng Zhang, Masato Mita, Mamoru Komachi*2023 · 3 citations*
109. **[One Refiner to Unlock Them All: Inference-Time Reasoning Elicitation via Reinforcement Query Refinement](https://md.research.elamur.ai/free/en/papers/zhou-2026-one-refiner-unlock-them-all/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yixiao Zhou, Dongzhou Cheng, Zhiliang wu, et al.*2026 · 2 citations*
110. **[CICL26 at SemEval-2026 Task 4: Narrative Story Similarity and Narrative Representation Learning](https://md.research.elamur.ai/free/en/papers/zhang-2026-cicl26-semeval-2026-task-4/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Wanzhao Zhang, Yue Yu*2026 · 1 citation*
111. **[CSRP: Chain-of-Thought Reasoning for Chinese Text Correction via Reinforcement Learning with Efficiency-Aware Rewards](https://md.research.elamur.ai/free/en/papers/tian-2026-csrp-chain-thought-reasoning-chinese/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wei Tian, Yuhao Zhou, Man Lan*2026 · 1 citation*
112. **[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*
113. **[Fine-Grained Detection of Context-Grounded Hallucinations Using LLMs](https://md.research.elamur.ai/free/en/papers/peisakhovsky-2026-fine-grained-detection-context-grounded/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yehonatan Peisakhovsky, Zorik Gekhman, Yosi Mass, et al.*2026 · 1 citation*
114. **[HARM: Learning Hate-Aware Reward Model for Evaluating Natural Language Explanations of Offensive Content](https://md.research.elamur.ai/free/en/papers/vecchi-2026-harm-learning-hate-aware-reward/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lorenzo Puppi Vecchi, Alceu de Souza Britto Jr, Emerson Cabrera Paraiso, et al.*2026 · 1 citation*
115. **[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*
116. **[When Vision-Language Models Judge Without Seeing: Exposing Informativeness Bias](https://md.research.elamur.ai/free/en/papers/zou-2026-when-vision-language-models-judge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaohan Zou, Roshan Sridhar, Mohammadtaher Safarzadeh, et al.*2026 · 1 citation*
117. **[Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models](https://md.research.elamur.ai/free/en/papers/mammen-2026-who-endorsed-it-measuring-authority/) [Workshop on Generation, Evaluation and Metrics (GEM)](https://md.research.elamur.ai/free/en/venues/gem/)**Priyanka Mary Mammen, Emil Joswin, Shankar Venkitachalam*2026 · 1 citation*
118. **[AJ-Bench: Benchmarking Agent-as-a-Judge for Environment-Aware Evaluation](https://md.research.elamur.ai/free/en/papers/shi-2026-aj-bench-benchmarking-agent-as/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wentao Shi, Yu Wang, Yuyang Zhao, et al.*2026*
119. **[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*
120. **[Beyond Prompt Engineering: A Systematic Analysis of Prompt Lexical Sensitivity and Its Impacts on Quality](https://md.research.elamur.ai/free/en/papers/xie-2026-beyond-prompt-engineering-systematic-analysis/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qipeng Xie, Zi Liang, Jiafei Wu, et al.*2026*
121. **[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*
122. **[Controlling What You Share: Assessing Language Model Adherence to Privacy Preferences](https://md.research.elamur.ai/free/en/papers/ramirez-2026-controlling-what-you-share-assessing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Guillem Ramírez, Alexandra Birch, Ivan Titov*2026*
123. **[Convergent Demographic Utility Hierarchies: Geometry of Intersectional Values in LLMs](https://md.research.elamur.ai/free/en/papers/sainath-2026-convergent-demographic-utility-hierarchies-geometry/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Pravish Sainath*2026*
124. **[Corpora Generation for Urdu Grammatical Error Correction](https://md.research.elamur.ai/free/en/papers/ahad-2026-corpora-generation-urdu-grammatical-error/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Syed Ahad, Burhanuddin Aliasghar Ezzi, Muhammad Arsalan Hussain, et al.*2026*
125. **[Deep-Reporter: Deep Research for Grounded Multimodal Long-Form Generation](https://md.research.elamur.ai/free/en/papers/ye-2026-deep-reporter-deep-research-grounded/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fangda Ye, Kuicai Dong, Xie Zhifei, et al.*2026*
126. **[DeepSynth-Eval: Objectively Evaluating Information Consolidation in Deep Survey Writing](https://md.research.elamur.ai/free/en/papers/zhang-2026-deepsynth-eval-objectively-evaluating-information/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hongzhi Zhang, Yuanze Hu, Tinghai Zhang, et al.*2026*
127. **[Evaluating Cost-Efficiency of LLMs in a RAG Setup on Polish Wikipedia: Quality vs. Energy Consumption](https://md.research.elamur.ai/free/en/papers/smits-2026-evaluating-cost-efficiency-llms-rag/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Patrycja Smits, Tomasz Walkowiak*2026*
128. **[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*
129. **[From Isolated Scoring to Collaborative Ranking: A Comparison-Native Framework for LLM-Based Paper Evaluation](https://md.research.elamur.ai/free/en/papers/zheng-2026-isolated-scoring-collaborative-ranking-comparison/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Pujun Zheng, Jiacheng Yao, Jinquan Zheng, et al.*2026*
130. **[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*
131. **[Large Language Models Are Bad Dice Players: LLMs Struggle to Generate Random Numbers from Statistical Distributions](https://md.research.elamur.ai/free/en/papers/zhao-2026-large-language-models-are-bad/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Minda Zhao, Yilun Du, Mengyu Wang*2026*
132. **[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*
133. **[Mitigating Selection Bias in Large Language Models via Permutation-Aware GRPO](https://md.research.elamur.ai/free/en/papers/zheng-2026-mitigating-selection-bias-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jinquan Zheng, Jia Yuan, Jiacheng Yao, et al.*2026*
134. **[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*
135. **[SPARTA: Evaluating Reasoning Segmentation Robustness through Black-Box Adversarial Paraphrasing in Text Autoencoder Latent Space](https://md.research.elamur.ai/free/en/papers/zinkovich-2026-sparta-evaluating-reasoning-segmentation-robustness/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Viktoriia Zinkovich, Anton Antonov, Andrei Spiridonov, et al.*2026*
136. **[Synthetic Data Generation for Training Diversified Commonsense Reasoning Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-synthetic-data-generation-training-diversified/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianhui Zhang, Bei Peng, Danushka Bollegala*2026*
137. **[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*

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