---
title: "Qi Zhang — all works — Elamur Research"
description: "All 27 works of Qi Zhang in the Elamur Research library, the most cited first: our summaries where we have them, else the original."
canonical: "https://research.elamur.ai/free/en/authors/qi-zhang/works/"
---
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# Qi Zhang — all works

27 works · [← Qi Zhang](https://md.research.elamur.ai/free/en/authors/qi-zhang/)

1. **[Phrase Dependency Parsing for Opinion Mining](https://md.research.elamur.ai/free/en/papers/wu-2009-phrase-dependency-parsing-opinion-mining/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yuanbin Wu, Qi Zhang, Xuanjing Huang, et al.*2009 · 423 citations*
2. [**InstructUIE: Multi-task Instruction Tuning for Unified Information Extraction arXiv:2304.08085**Xiao Wang, Weikang Zhou, Can Zu, et al.*2023 · 194 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-instructuie-multi-task-instruction-tuning/)
3. **[Template-free Prompt Tuning for Few-shot NER](https://md.research.elamur.ai/free/en/papers/ma-2022-template-free-prompt-tuning-few/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Ruotian Ma, Xin Zhou, Tao Gui, et al.*2022 · 182 citations*
4. **[TextFlint: Unified Multilingual Robustness Evaluation Toolkit for Natural Language Processing](https://md.research.elamur.ai/free/en/papers/wang-2021-textflint-unified-multilingual-robustness-evaluation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiao Wang, Qin Liu, Tao Gui, et al.*2021 · 147 citations*
5. **[Implicit Discourse Relation Detection via a Deep Architecture with Gated Relevance Network](https://md.research.elamur.ai/free/en/papers/chen-2016-implicit-discourse-relation-detection-deep/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jifan Chen, Qi Zhang, Pengfei Liu, et al.*2016 · 115 citations*
6. **[Calibrating LLM-Based Evaluator](https://md.research.elamur.ai/free/en/papers/liu-2024-calibrating-llm-based-evaluator/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Yuxuan Liu, Tianchi Yang, Shaohan Huang, et al.*2024 · 71 citations*
7. [**PanGu-Coder: Program Synthesis with Function-Level Language Modeling arXiv:2207.11280**Fenia Christopoulou, Gerasimos Lampouras, Milan Gritta, et al.*2022 · 49 citations*](https://md.research.elamur.ai/free/en/papers/christopoulou-2022-pangu-coder-program-synthesis/)
8. **[Unveiling Linguistic Regions in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2024-unveiling-linguistic-regions-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhihao Zhang, Jun Zhao, Qi Zhang, et al.*2024 · 39 citations*
9. **[UFO: A UI-Focused Agent for Windows OS Interaction](https://md.research.elamur.ai/free/en/papers/zhang-2025-ufo-ui-focused-agent-windows/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Chaoyun Zhang, Liqun Li, Shilin He, et al.*2025 · 38 citations*
10. **[ToolEyes: Fine-Grained Evaluation for Tool Learning Capabilities of Large Language Models in Real-world Scenarios](https://md.research.elamur.ai/free/en/papers/ye-2025-tooleyes-fine-grained-evaluation-tool/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Junjie Ye, Guanyu Li, SongYang Gao, et al.*2025 · 35 citations*
11. **[ToolHop: A Query-Driven Benchmark for Evaluating Large Language Models in Multi-Hop Tool Use](https://md.research.elamur.ai/free/en/papers/ye-2025-toolhop-query-driven-benchmark-evaluating/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junjie Ye, Zhengyin Du, Xuesong Yao, et al.*2025 · 15 citations*
12. **[Measuring Data Diversity for Instruction Tuning: A Systematic Analysis and A Reliable Metric](https://md.research.elamur.ai/free/en/papers/yang-2025-measuring-data-diversity-instruction-tuning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuming Yang, Yang Nan, Junjie Ye, et al.*2025 · 11 citations*
13. [**100 Days After DeepSeek-R1: A Survey on Replication Studies and More Directions for Reasoning Language Models arXiv:2505.00551**Chong Zhang, Yue Deng, Xiang Lin, et al.*2025 · 9 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2025-100-days-after-deepseek/)
14. **[Feedback-Driven Tool-Use Improvements in Large Language Models via Automated Build Environments](https://md.research.elamur.ai/free/en/papers/ye-2026-feedback-driven-tool-use-improvements/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Junjie Ye, Changhao Jiang, Zhengyin Du, et al.*2026 · 6 citations*
15. **[MulDimIF: A Multi-Dimensional Constraint Framework for Evaluating and Improving Instruction Following in Large Language Models](https://md.research.elamur.ai/free/en/papers/ye-2026-muldimif-multi-dimensional-constraint-framework/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Junjie Ye, Caishuang Huang, Zhuohan Chen, et al.*2026 · 4 citations*
16. **[OctoBench: Benchmarking Scaffold-Aware Instruction Following in Repository-Grounded Agentic Coding](https://md.research.elamur.ai/free/en/papers/ding-2026-octobench-benchmarking-scaffold-aware-instruction/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Deming Ding, Shichun Liu, Enhui Yang, et al.*2026 · 4 citations*
17. **[Metacognitive Self-Correction for Multi-Agent System via Prototype-Guided Next-Execution Reconstruction](https://md.research.elamur.ai/free/en/papers/shen-2026-metacognitive-self-correction-multi-agent/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xu Shen, Qi Zhang, Song Wang, et al.*2026 · 3 citations*
18. **[Outcome Accuracy is Not Enough: Aligning the Reasoning Process of Reward Models](https://md.research.elamur.ai/free/en/papers/wang-2026-outcome-accuracy-is-not-enough/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Binghai Wang, Yantao Liu, Yuxuan Liu, et al.*2026 · 3 citations*
19. **[Mnemis: Dual-Route Retrieval on Hierarchical Graphs for Long-Term LLM Memory](https://md.research.elamur.ai/free/en/papers/tang-2026-mnemis-dual-route-retrieval-hierarchical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zihao Tang, Xin Yu, Ziyu Xiao, et al.*2026 · 1 citation*
20. **[Unveiling the Deficiencies of Pre-trained Text-and-Layout Models in Real-world Visually-rich Document Information Extraction](https://md.research.elamur.ai/free/en/papers/zhang-2026-unveiling-deficiencies-pre-trained-text/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chong Zhang, Yixi Zhao, Yulu Xie, et al.*2026 · 1 citation*
21. **[Enhancing LLM-based Search Agents via Contribution Weighted Group Relative Policy Optimization](https://md.research.elamur.ai/free/en/papers/wang-2026-enhancing-llm-based-search-agents/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junzhe Wang, Zhiheng Xi, Yajie Yang, et al.*2026*
22. **[AgentGym2: Benchmarking Large Language Model Agents in De-Idealized Real-World Environments ↗](https://aclanthology.org/2026.acl-long.2058/) Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yet**Zhiheng Xi et al.*2026*
23. **[FinMRAGBench: A Realistic and Complex Benchmark for Multi-Modal RAG in Financial Document Analysis ↗](https://aclanthology.org/2026.findings-acl.187/) Findings of the Association for Computational Linguistics: ACL 2026 · no summary yet**Shouqing Yang et al.*2026*
24. **[AgentV-RL: Scaling Reward Modeling with Agentic Verifier ↗](https://aclanthology.org/2026.findings-acl.1156/) Findings of the Association for Computational Linguistics: ACL 2026 · no summary yet**Jiazheng Zhang et al.*2026*
25. **[REAP: Towards Effective Training-Free Chemical Reasoning with Explicit Atomic Priors ↗](https://aclanthology.org/2026.findings-acl.97/) Findings of the Association for Computational Linguistics: ACL 2026 · no summary yet**Mingxu Zhang et al.*2026*
26. **[Scaling Performance and Low-Resource Annotation with Many-Shot In-Context Learning for Named Entity Recognition ↗](https://aclanthology.org/2026.findings-acl.1431/) Findings of the Association for Computational Linguistics: ACL 2026 · no summary yet**Qi Zhang et al.*2026*
27. **[VRPO: Rethinking Value Modeling for Robust RL under Noisy Supervision in LLM Post-Training ↗](https://aclanthology.org/2026.acl-long.1103/) Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yet**Dingwei Zhu et al.*2026*