---
title: "Who cites Yunkai Zhang — 299 papers of our library"
description: "299 papers of the Elamur Research library cite the works of Yunkai Zhang, found in their bibliographies; the most cited first."
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---
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# Who cites Yunkai Zhang

299 citations of their works from 299 papers of our library (of the 149,439 whose bibliographies we read) · 63 with a page here, the most cited first · [← Yunkai Zhang](https://md.research.elamur.ai/free/en/authors/yunkai-zhang/)

1. **[A Survey of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,875 citations*
2. **[TaPas: Weakly Supervised Table Parsing via Pre-training](https://md.research.elamur.ai/free/en/papers/herzig-2020-tapas-weakly-supervised-table-parsing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jonathan Herzig, Pawel Krzysztof Nowak, Thomas Müller, et al.*2020 · 847 citations*
3. **[TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data](https://md.research.elamur.ai/free/en/papers/yin-2020-tabert-pretraining-joint-understanding-textual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Pengcheng Yin, Graham Neubig, Wen-tau Yih, et al.*2020 · 692 citations*
4. **[A Survey on Automated Fact-Checking](https://md.research.elamur.ai/free/en/papers/guo-2022-survey-automated-fact-checking/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Zhijiang Guo, Michael Schlichtkrull, Andreas Vlachos*2022 · 647 citations*
5. **[FinQA: A Dataset of Numerical Reasoning over Financial Data](https://md.research.elamur.ai/free/en/papers/chen-2021-finqa-dataset-numerical-reasoning-over/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhiyu Chen, Wenhu Chen, Charese Smiley, et al.*2021 · 513 citations*
6. **[ToTTo: A Controlled Table-To-Text Generation Dataset](https://md.research.elamur.ai/free/en/papers/parikh-2020-totto-controlled-table-text-generation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ankur Parikh, Xuezhi Wang, Sebastian Gehrmann, et al.*2020 · 482 citations*
7. [**HybridQA: A Dataset of Multi-Hop Question Answering over Tabular and Textual Data arXiv:2004.07347**Wenhu Chen, Hanwen Zha, Zhiyu Chen, et al.*2020 · 382 citations*](https://md.research.elamur.ai/free/en/papers/chen-2020-hybridqa-dataset-multi-hop-question/)
8. [**UL2: Unifying Language Learning Paradigms arXiv:2205.05131**Yi Tay, Mostafa Dehghani, Vinh Q. Tran, et al.*2022 · 347 citations*](https://md.research.elamur.ai/free/en/papers/tay-2022-ul2-unifying-language-learning-paradigms/)
9. **[Get Your Vitamin C! Robust Fact Verification with Contrastive Evidence](https://md.research.elamur.ai/free/en/papers/schuster-2021-get-your-vitamin-c-robust/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Tal Schuster, Adam Fisch, Regina Barzilay*2021 · 290 citations*
10. [**MiniCPM-V: A GPT-4V Level MLLM on Your Phone arXiv:2408.01800**Yuan Yao, Tianyu Yu, Ao Zhang, et al.*2024 · 269 citations*](https://md.research.elamur.ai/free/en/papers/yao-2024-minicpm-v-gpt-4v/)
11. [**TAPEX: Table Pre-training via Learning a Neural SQL Executor arXiv:2107.07653**Qian Liu, Bei Chen, Jiaqi Guo, et al.*2021 · 255 citations*](https://md.research.elamur.ai/free/en/papers/liu-2021-tapex-table-pre-training-learning/)
12. **[Table Meets LLM: Can Large Language Models Understand Structured Table Data? A Benchmark and Empirical Study](https://md.research.elamur.ai/free/en/papers/sui-2023-table-meets-llm-large-language/) [ACM International Conference on Web Search and Data Mining (WSDM)](https://md.research.elamur.ai/free/en/venues/acm-international-conference-on-web-search-and-data-mining-wsdm/)**Yuan Sui, Mengyu Zhou, Mingjie Zhou, et al.*2023 · 235 citations*
13. **[HoVer: A Dataset for Many-Hop Fact Extraction And Claim Verification](https://md.research.elamur.ai/free/en/papers/jiang-2020-hover-dataset-many-hop-fact/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yichen Jiang, Shikha Bordia, Zheng Zhong, et al.*2020 · 228 citations*
14. **[Monkey: Image Resolution and Text Label Are Important Things for Large Multi-modal Models](https://md.research.elamur.ai/free/en/papers/li-2023-monkey-image-resolution-text-label/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Zhang Li, Biao Yang, Qiang Liu, et al.*2023 · 222 citations*
15. **[CrossFit: A Few-shot Learning Challenge for Cross-task Generalization in NLP](https://md.research.elamur.ai/free/en/papers/ye-2021-crossfit-few-shot-learning-challenge/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Qinyuan Ye, Bill Yuchen Lin, Xiang Ren*2021 · 210 citations*
16. **[Logical Natural Language Generation from Open-Domain Tables](https://md.research.elamur.ai/free/en/papers/chen-2020-logical-natural-language-generation-open/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenhu Chen, Jianshu Chen, Yu Su, et al.*2020 · 210 citations*
17. **[That is a Known Lie: Detecting Previously Fact-Checked Claims](https://md.research.elamur.ai/free/en/papers/shaar-2020-that-is-known-lie-detecting/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shaden Shaar, Nikolay Babulkov, Giovanni Da San Martino, et al.*2020 · 193 citations*
18. **[A Survey on Stance Detection for Mis- and Disinformation Identification](https://md.research.elamur.ai/free/en/papers/hardalov-2022-survey-stance-detection-mis-disinformation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Momchil Hardalov, Arnav Arora, Preslav Nakov, et al.*2022 · 188 citations*
19. **[Large Language Models are few(1)-shot Table Reasoners](https://md.research.elamur.ai/free/en/papers/chen-2023-large-language-models-are-few/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenhu Chen*2023 · 182 citations*
20. [**Open Question Answering over Tables and Text arXiv:2010.10439**Wenhu Chen, Ming-Wei Chang, Eva Schlinger, et al.*2020 · 182 citations*](https://md.research.elamur.ai/free/en/papers/chen-2020-open-question-answering-over-tables/)
21. [**Binding Language Models in Symbolic Languages arXiv:2210.02875**Zhoujun Cheng, Tianbao Xie, Peng Shi, et al.*2022 · 170 citations*](https://md.research.elamur.ai/free/en/papers/cheng-2022-binding-language-models-symbolic-languages/)
22. **[Understanding tables with intermediate pre-training](https://md.research.elamur.ai/free/en/papers/eisenschlos-2020-understanding-tables-intermediate-pre-training/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Julian Eisenschlos, Syrine Krichene, Thomas Müller*2020 · 158 citations*
23. **[INFOTABS: Inference on Tables as Semi-structured Data](https://md.research.elamur.ai/free/en/papers/gupta-2020-infotabs-inference-tables-as-semi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Vivek Gupta, Maitrey Mehta, Pegah Nokhiz, et al.*2020 · 150 citations*
24. **[UniK-QA: Unified Representations of Structured and Unstructured Knowledge for Open-Domain Question Answering](https://md.research.elamur.ai/free/en/papers/oguz-2022-unik-qa-unified-representations-structured/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Barlas Oguz, Xilun Chen, Vladimir Karpukhin, et al.*2022 · 147 citations*
25. [**DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding arXiv:2412.10302**Zhiyu Wu, Xiaokang Chen, Zizheng Pan, et al.*2024 · 137 citations*](https://md.research.elamur.ai/free/en/papers/wu-2024-deepseek-vl2-mixture-experts/)
26. **[Natural Language Reasoning, A Survey](https://md.research.elamur.ai/free/en/papers/yu-2023-natural-language-reasoning-survey/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Fei Yu, Hongbo Zhang, Prayag Tiwari, et al.*2023 · 130 citations*
27. **[UReader: Universal OCR-free Visually-situated Language Understanding with Multimodal Large Language Model](https://md.research.elamur.ai/free/en/papers/ye-2023-ureader-universal-ocr-free-visually/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiabo Ye, Anwen Hu, Haiyang Xu, et al.*2023 · 129 citations*
28. **[mPLUG-DocOwl 1.5: Unified Structure Learning for OCR-free Document Understanding](https://md.research.elamur.ai/free/en/papers/hu-2024-mplug-docowl-1-5-unified/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Anwen Hu, Haiyang Xu, Jiabo Ye, et al.*2024 · 111 citations*
29. [**Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding arXiv:2401.04398**Zilong Wang, Hao Zhang, Chun-Liang Li, et al.*2024 · 105 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-chain-table-evolving-tables-reasoning/)
30. **[DialFact: A Benchmark for Fact-Checking in Dialogue](https://md.research.elamur.ai/free/en/papers/gupta-2022-dialfact-benchmark-fact-checking-dialogue/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Prakhar Gupta, Chien-Sheng Wu, Wenhao Liu, et al.*2022 · 97 citations*
31. **[Self-Checker: Plug-and-Play Modules for Fact-Checking with Large Language Models](https://md.research.elamur.ai/free/en/papers/li-2024-self-checker-plug-play-modules/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Miaoran Li, Baolin Peng, Michel Galley, et al.*2024 · 87 citations*
32. [**TableLlama: Towards Open Large Generalist Models for Tables arXiv:2311.09206**Tianshu Zhang, Xiang Yue, Yifei Li, et al.*2023 · 82 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-tablellama-towards-open-large-generalist/)
33. **[mPLUG-DocOwl2: High-resolution Compressing for OCR-free Multi-page Document Understanding](https://md.research.elamur.ai/free/en/papers/hu-2025-mplug-docowl2-high-resolution-compressing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Anwen Hu, Haiyang Xu, Liang Zhang, et al.*2025 · 62 citations*
34. **[Multimodal Table Understanding](https://md.research.elamur.ai/free/en/papers/zheng-2024-multimodal-table-understanding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mingyu Zheng, Xinwei Feng, Qingyi Si, et al.*2024 · 62 citations*
35. [**InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Output arXiv:2407.03320**Pan Zhang, Xiaoyi Dong, Yuhang Zang, et al.*2024 · 39 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-internlm-xcomposer-2-5/)
36. **[Exploring the Numerical Reasoning Capabilities of Language Models: A Comprehensive Analysis on Tabular Data](https://md.research.elamur.ai/free/en/papers/akhtar-2023-exploring-numerical-reasoning-capabilities-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mubashara Akhtar, Abhilash Shankarampeta, Vivek Gupta, et al.*2023 · 38 citations*
37. [**Through the Lens of Core Competency: Survey on Evaluation of Large Language Models arXiv:2308.07902**Ziyu Zhuang, Qiguang Chen, Longxuan Ma, et al.*2023 · 35 citations*](https://md.research.elamur.ai/free/en/papers/zhuang-2023-through-lens-core-competency-survey/)
38. **[Table-Critic: A Multi-Agent Framework for Collaborative Criticism and Refinement in Table Reasoning](https://md.research.elamur.ai/free/en/papers/yu-2025-table-critic-multi-agent-framework/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Peiying Yu, Guoxin Chen, Jingjing Wang*2025 · 25 citations*
39. [**MiniCPM-V 4.5: Cooking Efficient MLLMs via Architecture, Data, and Training Recipe arXiv:2509.18154**Tianyu Yu, Zefan Wang, Chongyi Wang, et al.*2025 · 24 citations*](https://md.research.elamur.ai/free/en/papers/yu-2025-minicpm-v-4-5/)
40. [**From Zero to Hero: Examining the Power of Symbolic Tasks in Instruction Tuning arXiv:2304.07995**Qian Liu, Fan Zhou, Zhengbao Jiang, et al.*2023 · 24 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-zero-hero-examining-power-symbolic/)
41. **[SciVer: Evaluating Foundation Models for Multimodal Scientific Claim Verification](https://md.research.elamur.ai/free/en/papers/wang-2025-sciver-evaluating-foundation-models-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chengye Wang, Yifei Shen, Zexi Kuang, et al.*2025 · 11 citations*
42. **[TableLoRA: Low-rank Adaptation on Table Structure Understanding for Large Language Models](https://md.research.elamur.ai/free/en/papers/he-2025-tablelora-low-rank-adaptation-table/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinyi He, Yihao Liu, Mengyu Zhou, et al.*2025 · 8 citations*
43. **[TableEval: A Real-World Benchmark for Complex, Multilingual, and Multi-Structured Table Question Answering](https://md.research.elamur.ai/free/en/papers/zhu-2025-tableeval-real-world-benchmark-complex/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Junnan Zhu, Jingyi Wang, Bohan Yu, et al.*2025 · 7 citations*
44. **[TANQ: An Open Domain Dataset of Table Answered Questions](https://md.research.elamur.ai/free/en/papers/akhtar-2025-tanq-open-domain-dataset-table/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Mubashara Akhtar, Chenxi Pang, Andreea Marzoca, et al.*2025 · 7 citations*
45. **[Weaver: Interweaving SQL and LLM for Table Reasoning](https://md.research.elamur.ai/free/en/papers/khoja-2025-weaver-interweaving-sql-llm-table/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Rohit Khoja, Devanshu Gupta, Yanjie Fu, et al.*2025 · 6 citations*
46. **[RAG over Tables: Hierarchical Memory Index, Multi-Stage Retrieval, and Benchmarking](https://md.research.elamur.ai/free/en/papers/zou-2026-rag-over-tables-hierarchical-memory/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiaru Zou, Dongqi Fu, Sirui Chen, et al.*2026 · 3 citations*
47. **[TabularMath: Understanding Math Reasoning over Tables with Large Language Models](https://md.research.elamur.ai/free/en/papers/tian-2026-tabularmath-understanding-math-reasoning-over/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shi-Yu Tian, Zhi Zhou, Wei Dong, et al.*2026 · 3 citations*
48. **[ClaimDB: A Fact Verification Benchmark over Large Structured Data](https://md.research.elamur.ai/free/en/papers/theologitis-2026-claimdb-fact-verification-benchmark-over/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Michael Theologitis, Preetam Prabhu Srikar Dammu, Chirag Shah, et al.*2026 · 2 citations*
49. **[Exploring Generative Process Reward Modeling for Semi-Structured Data: A Case Study of Table Question Answering](https://md.research.elamur.ai/free/en/papers/tang-2026-exploring-generative-process-reward-modeling/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Lei Tang, Wei Zhou, Mohsen Mesgar*2026 · 2 citations*
50. **[Table Question Answering in the Era of Large Language Models: A Comprehensive Survey of Tasks, Methods, and Evaluation](https://md.research.elamur.ai/free/en/papers/zhou-2026-table-question-answering-era-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wei Zhou, Bolei Ma, Annemarie Friedrich, et al.*2026 · 2 citations*
51. [**AraTable: Benchmarking LLMs' Reasoning and Understanding of Arabic Tabular Data arXiv:2507.18442**Rana Alshaikh, Israa Alghanmi, Shelan Jeawak*2025 · 2 citations*](https://md.research.elamur.ai/free/en/papers/alshaikh-2025-aratable-benchmarking-llms-reasoning-understanding/)
52. **[CoReTab: Improving Multimodal Table Understanding with Code-driven Reasoning](https://md.research.elamur.ai/free/en/papers/nguyen-2026-coretab-improving-multimodal-table-understanding/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Van-Quang Nguyen, Takayuki Okatani*2026 · 1 citation*
53. **[Efficient Table Retrieval and Understanding with Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/xu-2026-efficient-table-retrieval-understanding-multimodal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhuoyan Xu, Haoyang Fang, Boran Han, et al.*2026 · 1 citation*
54. **[A Survey of Multimodal Mathematical Reasoning: From Perception, Alignment to Reasoning](https://md.research.elamur.ai/free/en/papers/yang-2026-survey-multimodal-mathematical-reasoning-perception/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianyu Yang, Sihong Wu, Yilun Zhao, et al.*2026*
55. **[Can LLMs Self-Correct Table Reasoning Errors?](https://md.research.elamur.ai/free/en/papers/shaikh-2026-can-llms-self-correct-table/) [Workshop on Structured Understanding, Retrieval, and Generation in the LLM Era](https://md.research.elamur.ai/free/en/venues/surgellm/)**Farseen Shaikh*2026*
56. **[CompTab: A Comprehensive Benchmark for Real-World TableQA with Complex Reasoning and Irregular Tables](https://md.research.elamur.ai/free/en/papers/yang-2026-comptab-comprehensive-benchmark-real-world/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhen Yang, Wei Du, Jie Wang, et al.*2026*
57. **[Evidence Grounding vs. Memorization: Why Neural Semantics Matter for Knowledge Graph Fact Verification](https://md.research.elamur.ai/free/en/papers/upadhyay-2026-evidence-grounding-vs-memorization-why/) [Fact Extraction and VERification Workshop (FEVER)](https://md.research.elamur.ai/free/en/venues/fever/)**Ankit Kumar Upadhyay, John S. Erickson, Deborah L. McGuinness*2026*
58. **[Mixture-of-Minds: Multi-Agent Reinforcement Learning for Table Understanding](https://md.research.elamur.ai/free/en/papers/zhou-2026-mixture-minds-multi-agent-reinforcement/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuhang Zhou, Mingrui Zhang, Ke Li, et al.*2026*
59. **[Questionnaire Meets LLM: A Benchmark and Empirical Study of Structural Skills for Understanding Questions and Responses](https://md.research.elamur.ai/free/en/papers/nguyen-2026-questionnaire-meets-llm-benchmark-empirical/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Duc-Hai Nguyen, Vijayakumar Nanjappan, Barry O'Sullivan, et al.*2026*
60. **[Table-R1: Region-based Reinforcement Learning for Table Understanding](https://md.research.elamur.ai/free/en/papers/wu-2026-table-r1-region-based-reinforcement/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhenhe Wu, Jian Yang, Zhongjiang He, et al.*2026*
61. **[TableVista: Benchmarking Multimodal Table Reasoning under Visual and Structural Complexity](https://md.research.elamur.ai/free/en/papers/yang-2026-tablevista-benchmarking-multimodal-table-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zheyuan Yang, Liqiang Shang, Junjie Chen, et al.*2026*
62. **[Thesis Proposal: Intentional Inference for Insight Generation](https://md.research.elamur.ai/free/en/papers/onderkova-2026-thesis-proposal-intentional-inference-insight/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kristýna Onderková*2026*
63. **[Towards Robust Real-World Spreadsheet Understanding with Multi-Agent Multi-Format Reasoning](https://md.research.elamur.ai/free/en/papers/ren-2026-robust-real-world-spreadsheet-understanding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Houxing Ren, Mingjie Zhan, Zimu Lu, et al.*2026*

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