---
title: "Zhijiang Guo — papers of 2024 — 6 papers, the most cited first"
description: "Zhijiang Guo — papers of 2024: 6 papers on Elamur Research, the most cited first — what each work is about in our own words."
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# Zhijiang Guo — papers of 2024 — 6 papers, the most cited first

6 papers · [all years of Zhijiang Guo](https://md.research.elamur.ai/free/en/authors/zhijiang-guo/#years)

**[Knowledge Conflicts for LLMs: A Survey](https://md.research.elamur.ai/free/en/papers/xu-2024-knowledge-conflicts-llms-survey/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Rongwu Xu, Zehan Qi, Zhijiang Guo, et al.*2024 · 182 citations*

- [Aligning with Human Judgement: The Role of Pairwise Preference in Large Language Model Evaluators arXiv:2403.16950](https://md.research.elamur.ai/free/en/papers/liu-2024-aligning-human-judgement-role-pairwise/) — Yinhong Liu, Han Zhou, Zhijiang Guo, et al. · 2024 · 76 citations

**[ProxyQA: An Alternative Framework for Evaluating Long-Form Text Generation with Large Language Models](https://md.research.elamur.ai/free/en/papers/tan-2024-proxyqa-alternative-framework-evaluating-long/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haochen Tan, Zhijiang Guo, Zhan Shi, et al.*2024 · 30 citations*

**[AutoPSV: Automated Process-Supervised Verifier](https://md.research.elamur.ai/free/en/papers/lu-2024-autopsv-automated-process-supervised-verifier/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jianqiao Lu, Zhiyang Dou, Hongru Wang, et al.*2024 · 28 citations*

- [FormalAlign: Automated Alignment Evaluation for Autoformalization arXiv:2410.10135](https://md.research.elamur.ai/free/en/papers/lu-2024-formalalign-automated-alignment-evaluation-autoformalization/) — Jianqiao Lu, Yingjia Wan, Yinya Huang, et al. · 2024 · 18 citations
- [EffiCoder: Enhancing Code Generation in Large Language Models through Efficiency-Aware Fine-tuning arXiv:2410.10209](https://md.research.elamur.ai/free/en/papers/huang-2024-efficoder-enhancing-code-generation-large/) — Dong Huang, Guangtao Zeng, Jianbo Dai, et al. · 2024 · 11 citations