---
title: "Who cites Cheng Zhang — 52 papers of our library"
description: "52 papers of the Elamur Research library cite the works of Cheng Zhang, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/cheng-zhang/cited-by/"
---
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# Who cites Cheng Zhang

53 citations of their works from 52 papers of our library (of the 149,439 whose bibliographies we read) · 20 with a page here, the most cited first · [← Cheng Zhang](https://md.research.elamur.ai/free/en/authors/cheng-zhang/)

1. **[Calibrating Verbal Uncertainty as a Linear Feature to Reduce Hallucinations](https://md.research.elamur.ai/free/en/papers/ji-2025-calibrating-verbal-uncertainty-as-linear/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ziwei Ji, Lei Yu, Yeskendir Koishekenov, et al.*2025 · 11 citations*
2. [**ERNIE 5.0 Technical Report arXiv:2602.04705**Haifeng Wang, Hua Wu, Tian Wu, et al.*2026 · 7 citations*](https://md.research.elamur.ai/free/en/papers/wang-2026-ernie-5-0-technical/)
3. **[MetaFaith: Faithful Natural Language Uncertainty Expression in LLMs](https://md.research.elamur.ai/free/en/papers/liu-2025-metafaith-faithful-natural-language-uncertainty/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Gabrielle Kaili-May Liu, Gal Yona, Avi Caciularu, et al.*2025 · 6 citations*
4. **[Anthropomimetic Uncertainty: What Verbalized Uncertainty in Language Models is Missing](https://md.research.elamur.ai/free/en/papers/ulmer-2026-anthropomimetic-uncertainty-what-verbalized-uncertainty/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Dennis Ulmer, Alexandra Lorson, Ivan Titov, et al.*2026 · 4 citations*
5. **[Explaining Sources of Uncertainty in Automated Fact-Checking](https://md.research.elamur.ai/free/en/papers/sun-2026-explaining-sources-uncertainty-automated-fact/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingyi Sun, Greta Warren, Irina Shklovski, et al.*2026 · 3 citations*
6. **[AutoMonitor-Bench: Evaluating the Reliability of LLM-Based Misbehavior Monitor](https://md.research.elamur.ai/free/en/papers/yang-2026-automonitor-bench-evaluating-reliability-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shu Yang, Jingyu Hu, Tong Li, et al.*2026 · 2 citations*
7. **[Meeseeks: A Feedback-Driven, Iterative Self-Correction Benchmark evaluating LLMs' Instruction Following Capability](https://md.research.elamur.ai/free/en/papers/wang-2026-meeseeks-feedback-driven-iterative-self/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiaming Wang, Yunke Zhao, Peng Ding, et al.*2026 · 1 citation*
8. [**MÖVE: A Holistic LLM Benchmark for the German Public Sector arXiv:2606.13111**Camilla Dalerci, Thilo Michael, Robin Schaefer, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/dalerci-2026-m-ove-holistic-llm-benchmark/)
9. **[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*
10. **[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*
11. **[CFQA: A Chinese Financial Question Answering Benchmark from Corporate Annual Reports](https://md.research.elamur.ai/free/en/papers/zhu-2026-cfqa-chinese-financial-question-answering/) [Financial Narrative Processing Workshop](https://md.research.elamur.ai/free/en/venues/fnp/)**Tianning Zhu, Mo Liu, Murathan Kurfali*2026*
12. **[FineSteer: A Unified Framework for Fine-Grained Inference-Time Steering in Large Language Models](https://md.research.elamur.ai/free/en/papers/weng-2026-finesteer-unified-framework-fine-grained/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zixuan Weng, Jinghuai Zhang, Kunlin Cai, et al.*2026*
13. **[GPT-NL Public Corpus: A Permissively Licensed, Dutch-First Dataset for LLM Pre-training](https://md.research.elamur.ai/free/en/papers/oort-2026-gpt-nl-public-corpus-permissively/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Jesse J. Van Oort, Frank Brinkkemper, Erik de Graaf, et al.*2026*
14. **[GrACE: A Generative Approach to Better Confidence Elicitation and Efficient Test-Time Scaling in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-grace-generative-approach-better-confidence/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhaohan Zhang, Ziquan Liu, Ioannis Patras*2026*
15. **[HalluAudio: A Comprehensive Benchmark for Hallucination Detection in Large Audio-Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2026-halluaudio-comprehensive-benchmark-hallucination-detection/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Feiyu Zhao, Yiming Chen, Wenhuan Lu, et al.*2026*
16. **[KGHaluBench: A Knowledge Graph-Based Hallucination Benchmark for Evaluating the Breadth and Depth of LLM Knowledge](https://md.research.elamur.ai/free/en/papers/robertson-2026-kghalubench-knowledge-graph-based-hallucination/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Alex Robertson, Huizhi Liang, Mahbub Gani, et al.*2026*
17. **[POaaS: Minimal-Edit Prompt Optimization as a Service to Lift Accuracy and Cut Hallucinations on On-Device sLLMs](https://md.research.elamur.ai/free/en/papers/shim-2026-poaas-minimal-edit-prompt-optimization/) [Fact Extraction and VERification Workshop (FEVER)](https://md.research.elamur.ai/free/en/venues/fever/)**Jungwoo Shim, Dae Won Kim, Sunwook Kim, et al.*2026*
18. **[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*
19. **[ReFACT: A Benchmark for Scientific Confabulation Detection with Positional Error Annotations](https://md.research.elamur.ai/free/en/papers/wang-2026-refact-benchmark-scientific-confabulation-detection/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Yindong Wang, Martin Preiß, Margarita Bugueño, et al.*2026*
20. **[Rethinking Text-to-SQL: Dynamic Multi-turn SQL Interaction for Real-world Database Exploration](https://md.research.elamur.ai/free/en/papers/sun-2026-rethinking-text-sql-dynamic-multi/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Linzhuang Sun, Tianyu Guo, Hao Liang, et al.*2026*

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

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