---
title: "Who cites Juno Zhu — 105 papers of our library"
description: "105 papers of the Elamur Research library cite the works of Juno Zhu, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/juno-zhu/cited-by/"
---
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# Who cites Juno Zhu

105 citations of their works from 105 papers of our library (of the 149,439 whose bibliographies we read) · 34 with a page here, the most cited first · [← Juno Zhu](https://md.research.elamur.ai/free/en/authors/juno-zhu/)

1. [**TrustLLM: Trustworthiness in Large Language Models arXiv:2401.05561**Yue Huang, Lichao Sun, Haoran Wang, et al.*2024 · 237 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-trustllm-trustworthiness-large-language-models/)
2. **[Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs](https://md.research.elamur.ai/free/en/papers/jin-2024-graph-chain-thought-augmenting-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Bowen Jin, Chulin Xie, Jiawei Zhang, et al.*2024 · 89 citations*
3. **[Direct Judgement Preference Optimization](https://md.research.elamur.ai/free/en/papers/wang-2025-direct-judgement-preference-optimization/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**PeiFeng Wang, Austin Xu, Yilun Zhou, et al.*2025 · 35 citations*
4. **[RAGEval: Scenario Specific RAG Evaluation Dataset Generation Framework](https://md.research.elamur.ai/free/en/papers/zhu-2025-rageval-scenario-specific-rag-evaluation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kunlun Zhu, Yifan Luo, Dingling Xu, et al.*2025 · 34 citations*
5. **[MIRAGE-Bench: Automatic Multilingual Benchmark Arena for Retrieval-Augmented Generation Systems](https://md.research.elamur.ai/free/en/papers/thakur-2025-mirage-bench-automatic-multilingual-benchmark/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Nandan Thakur, Suleman Kazi, Ge Luo, et al.*2025 · 15 citations*
6. **[Does Context Matter? ContextualJudgeBench for Evaluating LLM-based Judges in Contextual Settings](https://md.research.elamur.ai/free/en/papers/xu-2025-does-context-matter-contextualjudgebench-evaluating/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Austin Xu, Srijan Bansal, Yifei Ming, et al.*2025 · 14 citations*
7. **[Sacred or Synthetic? Evaluating LLM Reliability and Abstention for Religious Questions](https://md.research.elamur.ai/free/en/papers/atif-2025-sacred-synthetic-evaluating-llm-reliability/) [Proceedings of the AAAI/ACM Conference on AI Ethics and Society](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-acm-conference-on-ai-ethics-and-society/)**Farah Atif, Nursultan Askarbekuly, Kareem Darwish, et al.*2025 · 8 citations*
8. [**HalluTruthQA: A Fine-Grained Benchmark for Hallucination Detection, Localization, and Explanation in Arabic Question Answering arXiv:2607.20219**Abdessalam Bouchekif; Mohammed-En-Nadhir Zighem; Salah Eddine Bekhouche; Hichem Telli; Somaya Eltanbouly; Shahd Gaben; Heba Sbahi; Samer Rashwani; Mutaz Al-Khatib; Emad Mohamed; Mohammed Ghaly;, Abdenour Hadid*2026 · 3 citations*](https://md.research.elamur.ai/free/en/papers/bouchekif-2026-hallutruthqa-fine-grained-benchmark-hallucination/)
9. **[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*
10. **[Context-Fidelity Boosting: Enhancing Faithful Generation through Watermark-Inspired Decoding](https://md.research.elamur.ai/free/en/papers/zhang-2026-context-fidelity-boosting-enhancing-faithful/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Weixu Zhang, Fanghua Ye, Qiang Gao, et al.*2026 · 1 citation*
11. **[FaithLens: Detecting and Explaining Faithfulness Hallucination](https://md.research.elamur.ai/free/en/papers/si-2026-faithlens-detecting-explaining-faithfulness-hallucination/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shuzheng Si, Qingyi Wang, Haozhe Zhao, et al.*2026 · 1 citation*
12. **[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*
13. **[HAD: HAllucination Detection Language Models Based on a Comprehensive Hallucination Taxonomy](https://md.research.elamur.ai/free/en/papers/xu-2026-had-hallucination-detection-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fan Xu, Xinyu Hu, Zhenghan Yu, et al.*2026 · 1 citation*
14. [**HalluTruthQA-4K: A Fine-Grained Corpus and Annotation Process for Arabic Hallucination Detection and Truth Verification arXiv:2608.03966**Salah Eddine Bekhouche; Abdessalam Bouchekif; Hichem Telli; Mohammed-En-Nadhir Zighem;, Abdenour Hadid*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/bekhouche-2026-hallutruthqa-4k-fine-grained-corpus/)
15. **[RAGVUE: A Diagnostic View for Explainable and Automated Evaluation of Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/murugaraj-2026-ragvue-diagnostic-view-explainable-automated/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Keerthana Murugaraj, Salima Lamsiyah, Martin Theobald*2026 · 1 citation*
16. **[Benchmarking Query-Conditioned Natural Language Inference](https://md.research.elamur.ai/free/en/papers/canby-2025-benchmarking-query-conditioned-natural-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Marc E. Canby, Xinchi Chen, Xing Niu, et al.*2025 · 1 citation*
17. **[A multilingual hallucination benchmark](https://md.research.elamur.ai/free/en/papers/thoresen-2026-multilingual-hallucination-benchmark/) [Workshop on the Role of Resources in the Age of Large Language Models](https://md.research.elamur.ai/free/en/venues/resourceful/)**Freja Thoresen, Dan Saattrup Smart*2026*
18. **[Benchmarking LLM's Capability in Reasoning over Conflicting Web References](https://md.research.elamur.ai/free/en/papers/yuan-2026-benchmarking-llm-s-capability-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yizhen Yuan, Rui Kong, Dongze Li, et al.*2026*
19. **[Causal Evidence Extraction and Triangulation in Crisis Reports using Large Language Models: A ReliefWeb-based Study](https://md.research.elamur.ai/free/en/papers/zhang-2026-causal-evidence-extraction-triangulation-crisis/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuanjun Zhang, Mourad Oussalah*2026*
20. **[CoDA: Restoring Contextual Dominance via Copy-Encouraged Attention Intervention for Mitigating RAG Hallucinations](https://md.research.elamur.ai/free/en/papers/shi-2026-coda-restoring-contextual-dominance-copy/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**JinWei Shi, Qizhuo Xie, Qianzi Hou, et al.*2026*
21. **[Constructing a Dataset for Hallucination Detection in Japanese Summarization with Fine-grained Faithfulness Labels](https://md.research.elamur.ai/free/en/papers/tanaka-2026-constructing-dataset-hallucination-detection-japanese/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Hikari Tanaka, Atsushi Keyaki, Mamoru Komachi*2026*
22. **[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*
23. **[DeepPavlov Strikes Back: A Toolkit for Improving LLM Reliability and Trustworthiness](https://md.research.elamur.ai/free/en/papers/nikolaev-2026-deeppavlov-strikes-back-toolkit-improving/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Evgenii Nikolaev, Timur Ionov, Anna Korzanova, et al.*2026*
24. **[HalluZig: Hallucination Detection using Zigzag Persistence](https://md.research.elamur.ai/free/en/papers/samaga-2026-halluzig-hallucination-detection-zigzag-persistence/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Shreyas N. Samaga, Gilberto Gonzalez Arroyo, Tamal K. Dey*2026*
25. [**Islamic Large Language Models: From Knowledge Acquisition to Trustworthy and Hallucination-Resistant AI arXiv:2606.16629**Mohammed Amine Mouhoub*2026*](https://md.research.elamur.ai/free/en/papers/mouhoub-2026-islamic-large-language-models-knowledge/)
26. **[LearnerCoMPASS: Intelligent Tutoring System with Dynamic Cognitive Diagnosis and Multi-Model Path Planning](https://md.research.elamur.ai/free/en/papers/sheng-2026-learnercompass-intelligent-tutoring-system-dynamic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziji Sheng, Guiyao Tie, Weidong Wang, et al.*2026*
27. **[Logic Matters in Lightweight Hallucination Classification for RAG System](https://md.research.elamur.ai/free/en/papers/yang-2026-logic-matters-lightweight-hallucination-classification/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ningyuan Yang, Kaizhu Huang*2026*
28. **[PRISM: Probing Reasoning, Instruction, and Source Memory in LLM Hallucinations](https://md.research.elamur.ai/free/en/papers/wu-2026-prism-probing-reasoning-instruction-source/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuhe Wu, Guangyu Wang, Yuran Chen, et al.*2026*
29. **[PROBE: PROcess-Based BEnchmark for Hallucination Detection](https://md.research.elamur.ai/free/en/papers/zhang-2026-probe-process-based-benchmark-hallucination/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yu Zhang, Peter Belcak, Shizhe Diao, et al.*2026*
30. **[RAG in the Wild: On the (In)effectiveness of LLMs with Mixture-of-Knowledge Retrieval Augmentation](https://md.research.elamur.ai/free/en/papers/xu-2026-rag-wild-effectiveness-llms-mixture/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ran Xu, Yuchen Zhuang, Yue Yu, et al.*2026*
31. **[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*
32. **[The Digital Dunning-Kruger Effect: Decoupling Hallucinations via Geometric Hidden-state Observation for Semantic Truthfulness](https://md.research.elamur.ai/free/en/papers/mao-2026-digital-dunning-kruger-effect-decoupling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yueheng Mao, Min Yu, Gengwang Li, et al.*2026*
33. **[TPA: Next Token Probability Attribution for Detecting Hallucinations in RAG](https://md.research.elamur.ai/free/en/papers/lu-2026-tpa-next-token-probability-attribution/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Pengqian Lu, Jie Lu, Anjin Liu, et al.*2026*
34. **[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*

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

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