---
title: "Who cites Qiji Zhou — 186 papers of our library"
description: "186 papers of the Elamur Research library cite the works of Qiji Zhou, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/qiji-zhou/cited-by/"
---
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# Who cites Qiji Zhou

186 citations of their works from 186 papers of our library (of the 141,840 whose bibliographies we read) · 20 with a page here, the most cited first · [← Qiji Zhou](https://md.research.elamur.ai/free/en/authors/qiji-zhou/)

1. **[A Survey on Evaluation of Large Language Models](https://md.research.elamur.ai/free/en/papers/chang-2023-survey-evaluation-large-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Yupeng Chang, Xu Wang, Jindong Wang, et al.*2023 · 3,641 citations*
2. **[Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/min-2021-recent-advances-natural-language-processing/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Bonan Min, Hayley Ross, Elior Sulem, et al.*2021 · 1,552 citations*
3. [**LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code arXiv:2403.07974**Naman Jain, King Han, Alex Gu, et al.*2024 · 540 citations*](https://md.research.elamur.ai/free/en/papers/jain-2024-livecodebench-holistic-contamination-free-evaluation/)
4. **[Dual Graph Convolutional Networks for Aspect-based Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/li-2021-dual-graph-convolutional-networks-aspect/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruifan Li, Hao Chen, Fangxiang Feng, et al.*2021 · 429 citations*
5. [**Logic-LM: Empowering Large Language Models with Symbolic Solvers for Faithful Logical Reasoning arXiv:2305.12295**Liangming Pan, Alon Albalak, Xinyi Wang, et al.*2023 · 370 citations*](https://md.research.elamur.ai/free/en/papers/pan-2023-logic-lm-empowering-large-language/)
6. [**PromptRobust: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts arXiv:2306.04528**Kaijie Zhu, Jindong Wang, Jiaheng Zhou, et al.*2023 · 303 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2023-promptrobust-towards-evaluating-robustness-large/)
7. **[Aspect-Category-Opinion-Sentiment Quadruple Extraction with Implicit Aspects and Opinions](https://md.research.elamur.ai/free/en/papers/cai-2021-aspect-category-opinion-sentiment-quadruple/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hongjie Cai, Rui Xia, Jianfei Yu*2021 · 255 citations*
8. [**TrustLLM: Trustworthiness in Large Language Models arXiv:2401.05561**Yue Huang, Lichao Sun, Haoran Wang, et al.*2024 · 226 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-trustllm-trustworthiness-large-language-models/)
9. [**Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment arXiv:2308.05374**Yang Liu; Yuanshun Yao; Jean-Francois Ton; Xiaoying Zhang; Ruocheng Guo; Hao Cheng; Yegor Klochkov; Muhammad Faaiz Taufiq;, Hang Li*2023 · 220 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-trustworthy-llms-survey-guideline-evaluating/)
10. [**Evaluating Large Language Models: A Comprehensive Survey arXiv:2310.19736**Zishan Guo, Renren Jin, Chuang Liu, et al.*2023 · 178 citations*](https://md.research.elamur.ai/free/en/papers/guo-2023-evaluating-large-language-models-comprehensive/)
11. **[Graph Pre-training for AMR Parsing and Generation](https://md.research.elamur.ai/free/en/papers/bai-2022-graph-pre-training-amr-parsing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xuefeng Bai, Yulong Chen, Yue Zhang*2022 · 153 citations*
12. [**Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and Mitigation arXiv:2305.15852**Niels Mundler, Jingxuan He, Slobodan Jenko, et al.*2023 · 150 citations*](https://md.research.elamur.ai/free/en/papers/mundler-2023-self-contradictory-hallucinations-large-language/)
13. [**SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models arXiv:2307.10635**Xiaoxuan Wang, Ziniu Hu, Pan Lu, et al.*2023 · 149 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-scibench-evaluating-college-level-scientific/)
14. **[Are Large Language Models Really Good Logical Reasoners? A Comprehensive Evaluation and Beyond](https://md.research.elamur.ai/free/en/papers/xu-2023-large-language-models-really-good/) [IEEE Transactions on Knowledge and Data Engineering](https://md.research.elamur.ai/free/en/venues/ieee-transactions-on-knowledge-and-data-engineering/)**Fangzhi Xu, Qika Lin, Jiawei Han, et al.*2023 · 141 citations*
15. [**CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution arXiv:2401.03065**Alex Gu, Baptiste Rozière, Hugh Leather, et al.*2024 · 113 citations*](https://md.research.elamur.ai/free/en/papers/gu-2024-cruxeval-benchmark-code-reasoning-understanding/)
16. **[Aligning Large and Small Language Models via Chain-of-Thought Reasoning](https://md.research.elamur.ai/free/en/papers/ranaldi-2024-aligning-large-small-language-models/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Leonardo Ranaldi, Andre Freitas*2024 · 70 citations*
17. [**Improving Arabic Diacritization with Regularized Decoding and Adversarial Training**Han Qin, Guimin Chen, Yuanhe Tian, et al.*2021 · 25 citations*](https://md.research.elamur.ai/free/en/papers/qin-2021-improving-arabic-diacritization-regularized-decoding/)
18. [**ParaAMR: A Large-Scale Syntactically Diverse Paraphrase Dataset by AMR Back-Translation**Kuan-Hao Huang, Varun Iyer, I-Hung Hsu, et al.*2023 · 24 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-paraamr-large-scale-syntactically-diverse/)
19. [**Unsupervised Syntactically Controlled Paraphrase Generation with Abstract Meaning Representations**Kuan-Hao Huang, Varun Iyer, Anoop Kumar, et al.*2022 · 15 citations*](https://md.research.elamur.ai/free/en/papers/huang-2022-unsupervised-syntactically-controlled-paraphrase-generation/)
20. [**T-STAR: Truthful Style Transfer using AMR Graph as Intermediate Representation**Anubhav Jangra, Preksha Nema, Aravindan Raghuveer*2022 · 11 citations*](https://md.research.elamur.ai/free/en/papers/jangra-2022-t-star-truthful-style-transfer/)

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

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