---
title: "Who cites Yuanzhuo Wang — 161 papers of our library"
description: "161 papers of the Elamur Research library cite the works of Yuanzhuo Wang, found in their bibliographies; the most cited first."
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---
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# Who cites Yuanzhuo Wang

182 citations of their works from 161 papers of our library (of the 149,439 whose bibliographies we read) · 20 with a page here, the most cited first · [← Yuanzhuo Wang](https://md.research.elamur.ai/free/en/authors/yuanzhuo-wang/)

1. **[Text Summarization with Pretrained Encoders](https://md.research.elamur.ai/free/en/papers/liu-2019-text-summarization-pretrained-encoders/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yang Liu, Mirella Lapata*2019 · 2,095 citations*
2. **[QuestEval: Summarization Asks for Fact-based Evaluation](https://md.research.elamur.ai/free/en/papers/scialom-2021-questeval-summarization-asks-fact-based/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Thomas Scialom, Paul-Alexis Dray, Sylvain Lamprier, et al.*2021 · 359 citations*
3. **[MAVEN: A Massive General Domain Event Detection Dataset](https://md.research.elamur.ai/free/en/papers/wang-2020-maven-massive-general-domain-event/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xiaozhi Wang, Ziqi Wang, Xu Han, et al.*2020 · 261 citations*
4. **[Extractive Summarization of Long Documents by Combining Global and Local Context](https://md.research.elamur.ai/free/en/papers/xiao-2019-extractive-summarization-long-documents-combining/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wen Xiao, Giuseppe Carenini*2019 · 214 citations*
5. **[Conditional Generation with a Question-Answering Blueprint](https://md.research.elamur.ai/free/en/papers/narayan-2023-conditional-generation-question-answering-blueprint/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Shashi Narayan, Joshua Maynez, Reinald Kim Amplayo, et al.*2023 · 70 citations*
6. **[FaithfulRAG: Fact-Level Conflict Modeling for Context-Faithful Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/zhang-2025-faithfulrag-fact-level-conflict-modeling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qinggang Zhang, Zhishang Xiang, Yilin Xiao, et al.*2025 · 27 citations*
7. **[A Reality Check on Context Utilisation for Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/hagstrom-2025-reality-check-context-utilisation-retrieval/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lovisa Hagström, Sara Vera Marjanovic, Haeun Yu, et al.*2025 · 13 citations*
8. **[ZoFia: Zero-Shot Fake News Detection with Entity-Guided Retrieval and Multi-LLM Interaction](https://md.research.elamur.ai/free/en/papers/wu-2026-zofia-zero-shot-fake-news/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lvhua Wu, Xuefeng Jiang, Sheng Sun, et al.*2026 · 3 citations*
9. **[BaseCal: Unsupervised Confidence Calibration via Base Model Signals](https://md.research.elamur.ai/free/en/papers/tan-2026-basecal-unsupervised-confidence-calibration-base/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hexiang Tan, Wanli Yang, Junwei Zhang, et al.*2026 · 1 citation*
10. **[Beyond Meta-Reasoning: Metacognitive Consolidation for Self-Improving LLM Reasoning](https://md.research.elamur.ai/free/en/papers/zhuang-2026-beyond-meta-reasoning-metacognitive-consolidation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziqing Zhuang, Linhai Zhang, Jiasheng Si, et al.*2026 · 1 citation*
11. **[CoAct: Co-Active LLM Preference Learning with Human-AI Synergy](https://md.research.elamur.ai/free/en/papers/xu-2026-coact-co-active-llm-preference/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruiyao Xu, Mihir Parmar, Tiankai Yang, et al.*2026 · 1 citation*
12. **[CoVerRL: Breaking the Consensus Trap in Label-Free Reasoning via Generator-Verifier Co-Evolution](https://md.research.elamur.ai/free/en/papers/pan-2026-coverrl-breaking-consensus-trap-label/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Teng Pan, Yuchen Yan, Zixuan Wang, et al.*2026 · 1 citation*
13. **[Whose Facts Win? LLM Source Preferences under Knowledge Conflicts](https://md.research.elamur.ai/free/en/papers/schuster-2026-whose-facts-win-llm-source/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jakob Schuster, Vagrant Gautam, Katja Markert*2026 · 1 citation*
14. **[Critic Rule Induction: Improving Temporal Knowledge Graph Forecasting with Generator-Critic Language Models](https://md.research.elamur.ai/free/en/papers/ning-2026-critic-rule-induction-improving-temporal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yingsong Ning, Fu Zhang, Jingwei Cheng, et al.*2026*
15. **[From Implicit Graph Encoding to Explicit Evidence: A Training-Free LLM Framework for Temporal Knowledge Graph Reasoning](https://md.research.elamur.ai/free/en/papers/tang-2026-implicit-graph-encoding-explicit-evidence/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Guo Tang, Ke Cheng, Huiming Fan, et al.*2026*
16. **[Learning Uncertainty from Sequential Internal Dispersion in Large Language Models](https://md.research.elamur.ai/free/en/papers/srey-2026-learning-uncertainty-sequential-internal-dispersion/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ponhvoan Srey, Xiaobao Wu, Cong-Duy T Nguyen, et al.*2026*
17. **[Logical Consistency as a Bridge: Improving LLM Hallucination Detection via Label Constraint Modeling between Responses and Self-Judgments](https://md.research.elamur.ai/free/en/papers/mi-2026-logical-consistency-as-bridge-improving/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Mi, Qiang Sheng, Shaofei Wang, et al.*2026*
18. **[When Facts Change: Temporal Knowledge Conflict Resolution in LLMs](https://md.research.elamur.ai/free/en/papers/wallat-2026-when-facts-change-temporal-knowledge/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jonas Wallat, Wolfgang Nejdl, Sandipan Sikdar*2026*
19. **[Research Progress and Trend of Temporal Knowledge Graph Representation and Reasoning (时序知识图谱表示与推理的研究进展与趋势)](https://md.research.elamur.ai/free/en/papers/wang-2024-trend-temporal-knowledge/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Yuhan Wang (王俞涵), Ziyang Chen (陈子阳), Xiang Zhao (赵翔), et al.*2024*
20. **[Survey on Representation Learning Methods of Knowledge Graph for Link Prediction (面向链接预测的知识图谱表示学习方法综述)](https://md.research.elamur.ai/free/en/papers/du-2023-representation-learning-methods/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Xueying Du (杜雪盈), Mingwei Liu (刘名威), Liwei Shen (沈立炜), et al.*2023*

141 more citing papers of our library have no page here yet.

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