---
title: "Who cites Haoning Wu — 258 papers of our library"
description: "258 papers of the Elamur Research library cite the works of Haoning Wu, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/haoning-wu/cited-by/"
---
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# Who cites Haoning Wu

267 citations of their works from 258 papers of our library (of the 149,439 whose bibliographies we read) · 62 with a page here, the most cited first · [← Haoning Wu](https://md.research.elamur.ai/free/en/authors/haoning-wu/)

1. [**Qwen2.5-VL Technical Report arXiv:2502.13923**Shuai Bai, Keqin Chen, Xuejing Liu, et al.*2025 · 1,031 citations*](https://md.research.elamur.ai/free/en/papers/bai-2025-qwen2-5-vl-technical/)
2. **[MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/fu-2023-mme-comprehensive-evaluation-benchmark-multimodal/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Chaoyou Fu, Peixian Chen, Yunhang Shen, et al.*2023 · 554 citations*
3. [**LLaVA-OneVision: Easy Visual Task Transfer arXiv:2408.03326**Bo Li, Yuanhan Zhang, Dong Guo, et al.*2024 · 477 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llava-onevision-easy-visual-task/)
4. **[Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis](https://md.research.elamur.ai/free/en/papers/fu-2024-video-mme-first-ever-comprehensive/) [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/)**Chaoyou Fu, Yuhan Dai, Yongdong Luo, et al.*2024 · 427 citations*
5. [**Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling arXiv:2412.05271**Zhe Chen, Weiyun Wang, Yue Cao, et al.*2024 · 287 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-expanding-performance-boundaries-open/)
6. [**InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models arXiv:2504.10479**Jinguo Zhu, Weiyun Wang, Zhe Chen, et al.*2025 · 216 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-internvl3-exploring-advanced-training/)
7. [**InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency arXiv:2508.18265**Weiyun Wang, Zhangwei Gao, Lixin Gu, et al.*2025 · 179 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-internvl3-5-advancing-open/)
8. **[MLVU: Benchmarking Multi-task Long Video Understanding](https://md.research.elamur.ai/free/en/papers/zhou-2024-mlvu-benchmarking-multi-task-long/) [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/)**Junjie Zhou, Yan Shu, Bo Zhao, et al.*2024 · 140 citations*
9. [**LLaVA-Video: Video Instruction Tuning With Synthetic Data arXiv:2410.02713**Yuanhan Zhang, Jinming Wu, Wei Li, et al.*2024 · 119 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-llava-video-video-instruction-tuning/)
10. [**GLM-5: from Vibe Coding to Agentic Engineering arXiv:2602.15763**Aohan Zeng, Xin Lv, Zhenyu Hou, et al.*2026 · 95 citations*](https://md.research.elamur.ai/free/en/papers/team-2026-5-glm-5-vibe-coding/)
11. [**GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning arXiv:2507.01006**GLM-V Team, Wenyi Hong, Wenmeng Yu, et al.*2025 · 89 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-v-glm-4-5v-glm/)
12. **[LVBench: An Extreme Long Video Understanding Benchmark](https://md.research.elamur.ai/free/en/papers/wang-2024-lvbench-extreme-long-video-understanding/) [IEEE/CVF International Conference on Computer Vision (ICCV)](https://md.research.elamur.ai/free/en/venues/ieee-cvf-international-conference-on-computer-vision-iccv/)**Weihan Wang, Zehai He, Wenyi Hong, et al.*2024 · 89 citations*
13. [**Kimi-VL Technical Report arXiv:2504.07491**Kimi Team, Angang Du, Bohong Yin, et al.*2025 · 70 citations*](https://md.research.elamur.ai/free/en/papers/kimi-team-2025-kimi-vl-technical-report/)
14. [**Seed1.5-VL Technical Report arXiv:2505.07062**Dong Guo, Faming Wu, Feida Zhu, et al.*2025 · 67 citations*](https://md.research.elamur.ai/free/en/papers/guo-2025-seed1-5-vl-technical/)
15. [**Kimi K2.5: Visual Agentic Intelligence arXiv:2602.02276**Kimi Team, Tongtong Bai, Yifan Bai, et al.*2026 · 66 citations*](https://md.research.elamur.ai/free/en/papers/kimi-team-2026-kimi-k2-5-visual/)
16. [**mPLUG-Owl3: Towards Long Image-Sequence Understanding in Multi-Modal Large Language Models arXiv:2408.04840**Jiabo Ye, Haiyang Xu, Haowei Liu, et al.*2024 · 60 citations*](https://md.research.elamur.ai/free/en/papers/ye-2024-mplug-owl3-towards-long-image/)
17. [**Kimi K3: Open Frontier Intelligence arXiv:2607.24653**Kimi Team, Tongtong Bai, Yifan Bai, et al.*2026 · 40 citations*](https://md.research.elamur.ai/free/en/papers/kimi-team-2026-kimi-k3-open-frontier/)
18. [**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/)
19. **[Video Compression Commander: Plug-and-Play Inference Acceleration for Video Large Language Models](https://md.research.elamur.ai/free/en/papers/liu-2025-video-compression-commander-plug-play/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xuyang Liu, Yiyu Wang, Junpeng Ma, et al.*2025 · 16 citations*
20. [**Qwen3-Coder-Next Technical Report arXiv:2603.00729**Ruisheng Cao, Mouxiang Chen, Jiawei Chen, et al.*2026 · 15 citations*](https://md.research.elamur.ai/free/en/papers/cao-2026-qwen3-coder-next-technical/)
21. **[Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models](https://md.research.elamur.ai/free/en/papers/xuan-2025-seeing-is-believing-but-how/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Weihao Xuan, Qingcheng Zeng, Heli Qi, et al.*2025 · 11 citations*
22. **[SpecVLM: Enhancing Speculative Decoding of Video LLMs via Verifier-Guided Token Pruning](https://md.research.elamur.ai/free/en/papers/ji-2025-specvlm-enhancing-speculative-decoding-video/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yicheng Ji, Jun Zhang, Heming Xia, et al.*2025 · 10 citations*
23. **[DRISHTIKON: A Multimodal Multilingual Benchmark for Testing Language Models' Understanding on Indian Culture](https://md.research.elamur.ai/free/en/papers/maji-2025-drishtikon-multimodal-multilingual-benchmark-testing/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Arijit Maji, Raghvendra Kumar, Akash Ghosh, et al.*2025 · 9 citations*
24. **[TrimTokenator: Towards Adaptive Visual Token Pruning for Large Multimodal Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-trimtokenator-adaptive-visual-token-pruning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hao Zhang, Lyu Mengsi, Chenrui He, et al.*2026 · 6 citations*
25. **[VideoPro: Adaptive Program Reasoning for Long Video Understanding](https://md.research.elamur.ai/free/en/papers/li-2026-videopro-adaptive-program-reasoning-long/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chenglin Li, Feng Han, Yikun Wang, et al.*2026 · 6 citations*
26. **[Visual Contextual Attack: Jailbreaking MLLMs with Image-Driven Context Injection](https://md.research.elamur.ai/free/en/papers/ziqi-2025-visual-contextual-attack-jailbreaking-mllms/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Miao Ziqi, Yi Ding, Lijun Li, et al.*2025 · 6 citations*
27. [**MiniCPM-o 4.5: Towards Real-Time Full-Duplex Omni-Modal Interaction arXiv:2604.27393**Junbo Cui, Bokai Xu, Chongyi Wang, et al.*2026 · 5 citations*](https://md.research.elamur.ai/free/en/papers/cui-2026-minicpm-o-4-5/)
28. **[Uncertainty Quantification in LLM Agents: Foundations, Emerging Challenges, and Opportunities](https://md.research.elamur.ai/free/en/papers/oh-2026-uncertainty-quantification-llm-agents-foundations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Changdae Oh, Seongheon Park, To Eun Kim, et al.*2026 · 4 citations*
29. [**DeepSeek-V4.1-Flash: Pushing the Limits of KV Cache Compression arXiv:2609.19969**DeepSeek-AI, Anyi Xu, B. Li, et al.*2026 · 3 citations*](https://md.research.elamur.ai/free/en/papers/deepseek-ai-2026-deepseek-v4-1-flash/)
30. **[From Charts to Code: A Hierarchical Benchmark for Multimodal Models](https://md.research.elamur.ai/free/en/papers/tang-2026-charts-code-hierarchical-benchmark-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiahao Tang, Henry Hengyuan Zhao, Lijian Wu, et al.*2026 · 3 citations*
31. **[SafeMT: Multi-turn Safety for Multimodal Language Models](https://md.research.elamur.ai/free/en/papers/zhu-2026-safemt-multi-turn-safety-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Han Zhu, Juntao Dai, Jiaming Ji, et al.*2026 · 3 citations*
32. **[SynthRL: Scaling Visual Reasoning with Verifiable Data Synthesis](https://md.research.elamur.ai/free/en/papers/wu-2026-synthrl-scaling-visual-reasoning-verifiable/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zijian Wu, Jinjie Ni, Xiangyan Liu, et al.*2026 · 3 citations*
33. **[BLEnD-Vis: Benchmarking Multimodal Cultural Understanding in Vision Language Models](https://md.research.elamur.ai/free/en/papers/tan-2026-blend-vis-benchmarking-multimodal-cultural/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Bryan Chen Zhengyu Tan, Weihua Zheng, Zhengyuan Liu, et al.*2026 · 2 citations*
34. [**MiniMax Sparse Attention arXiv:2606.13392**Xunhao Lai, Weiqi Xu, Yufeng Yang, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/lai-2026-minimax-sparse-attention/)
35. **[Sculpting the Vector Space: Towards Efficient Multi-Vector Visual Document Retrieval via Prune-then-Merge Framework](https://md.research.elamur.ai/free/en/papers/yan-2026-sculpting-vector-space-efficient-multi/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yibo Yan, Mingdong Ou, Yi Cao, et al.*2026 · 2 citations*
36. **[Sparrow: Text-Anchored Window Attention with Visual-Semantic Glimpsing for Speculative Decoding in Video LLMs](https://md.research.elamur.ai/free/en/papers/zhang-2026-sparrow-text-anchored-window-attention/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Libo Zhang, Zhaoning Zhang, Hongwanyang, et al.*2026 · 2 citations*
37. **[Agentic Very Long Video Understanding](https://md.research.elamur.ai/free/en/papers/rege-2026-agentic-very-long-video-understanding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Aniket Rege, Arka Sadhu, Yuliang Li, et al.*2026 · 1 citation*
38. **[KidsArtBench: Multi-Dimensional Children's Art Evaluation with Attribute-Aware MLLMs](https://md.research.elamur.ai/free/en/papers/ye-2026-kidsartbench-multi-dimensional-children-s/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Mingrui Ye, Chanjin Zheng, Zengyi Yu, et al.*2026 · 1 citation*
39. **[MMErroR: A Benchmark for Erroneous Reasoning in Vision-Language Models](https://md.research.elamur.ai/free/en/papers/shi-2026-mmerror-benchmark-erroneous-reasoning-vision/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yang Shi, Yifeng Xie, Minzhe Guo, et al.*2026 · 1 citation*
40. **[Seeing but Not Thinking: Routing Distraction in Multimodal Mixture-of-Experts](https://md.research.elamur.ai/free/en/papers/xu-2026-seeing-but-not-thinking-routing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haolei Xu, Haiwen Hong, Hongxing Li, et al.*2026 · 1 citation*
41. **[sutta at SemEval-2026 Task 12: A Multi-Perspective Retrieve-Verify-Aggregate Framework for Abductive Event Reasoning](https://md.research.elamur.ai/free/en/papers/zou-2026-sutta-semeval-2026-task-12/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Junliu Zou, Liang Yang, Jingjie Zeng*2026 · 1 citation*
42. **[TRACE: Evidence Grounding-Guided Multi-Video Event Understanding and Claim Generation](https://md.research.elamur.ai/free/en/papers/yan-2026-trace-evidence-grounding-guided-multi/) [Workshop on Multimodal Augmented Generation via Multimodal Retrieval](https://md.research.elamur.ai/free/en/venues/magmar/)**Pengyu Yan, Akhil V S S Gorugantu, Mahesh Bhosale, et al.*2026 · 1 citation*
43. [**A Cascade Reinforcement Learning Strategy for Efficiently Enhancing the Reasoning Ability of Multimodal Large Language Models (高效提升多模态大语言模型推理能力的级联强化学习策略) Acta Automatica Sinica (自动化学报)**Weiyun Wang (王玮赟), Hengjun Pu (蒲恒骏), Linglin Jing (景凌林), et al.*2026*](https://md.research.elamur.ai/free/en/papers/wang-2026-cascade-reinforcement-learning/)
44. **[Curriculum Learning based Hierarchical Scoring and Analysis Framework for Question Answering Task Evaluation](https://md.research.elamur.ai/free/en/papers/wu-2026-curriculum-learning-based-hierarchical-scoring/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qiong Wu, Tan Yue, Jianxin Liang, et al.*2026*
45. **[Data Foundations of Long-Context Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/sun-2026-data-foundations-long-context-language/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Zechen Sun, Yuyang Sun, Zhaochen Su, et al.*2026*
46. **[Does Chain-of-Thought Reasoning Help Mobile GUI Agents? An Empirical Study](https://md.research.elamur.ai/free/en/papers/zhang-2026-does-chain-thought-reasoning-help/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Li Zhang, Longxi Gao, Mengwei Xu*2026*
47. **[ExStrucTiny: A Benchmark for Schema-Variable Structured Information Extraction from Document Images](https://md.research.elamur.ai/free/en/papers/sibue-2026-exstructiny-benchmark-schema-variable-structured/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Mathieu Sibue, Andrés Muñoz Garza, Samuel Mensah, et al.*2026*
48. **[Fico: Evaluating Vision-Language Models under Visual Fidelity and Compression at Scale](https://md.research.elamur.ai/free/en/papers/tu-2026-fico-evaluating-vision-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jianhong Tu, Nicholas Crispino, Kyle Montgomery, et al.*2026*
49. **[GameplayQA: A Benchmarking Framework for Decision-Dense POV-Synced Multi-Video Understanding of 3D Virtual Agents](https://md.research.elamur.ai/free/en/papers/wang-2026-gameplayqa-benchmarking-framework-decision-dense/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yunzhe Wang, Runhui Xu, Kexin Zheng, et al.*2026*
50. **[How Adversarial Environments Mislead Agentic AI?](https://md.research.elamur.ai/free/en/papers/zhan-2026-how-adversarial-environments-mislead-agentic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhonghao Zhan, Huichi Zhou, Zhenhao Li, et al.*2026*
51. **[MT-Video-Bench: A Holistic Video Understanding Benchmark for Evaluating Multimodal LLMs in Multi-Turn Dialogues](https://md.research.elamur.ai/free/en/papers/pan-2026-mt-video-bench-holistic-video/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yaning Pan, Qianqian Xie, Guohui Zhang, et al.*2026*
52. **[MVP: Enhancing Video Large Language Models via Self-supervised Masked Video Prediction](https://md.research.elamur.ai/free/en/papers/sun-2026-mvp-enhancing-video-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaokun Sun, Zezhong Wu, Zewen Ding, et al.*2026*
53. **[PlotGen-Bench: Evaluating VLMs on Generating Visualization Code from Diverse Plots across Multiple Libraries](https://md.research.elamur.ai/free/en/papers/zhao-2026-plotgen-bench-evaluating-vlms-generating/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yi Zhao, Zhen Yang, Shuaiqi Duan, et al.*2026*
54. **[Putting Captions to the Test: Evaluating Video Caption Quality through Multiple-Choice Question Answering](https://md.research.elamur.ai/free/en/papers/wang-2026-putting-captions-test-evaluating-video/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zizhen Wang, Bo Feng, Zhengfeng Lai, et al.*2026*
55. [**Qwen-AgentWorld: Language World Models for General Agents arXiv:2606.24597**Yuxin Zuo, Zikai Xiao, Li Sheng, et al.*2026*](https://md.research.elamur.ai/free/en/papers/zuo-2026-qwen-agentworld-language-world/)
56. **[Reducing Token Redundancy in LVLMs: A Systematic Review of Token Pruning Methods](https://md.research.elamur.ai/free/en/papers/yuan-2026-reducing-token-redundancy-lvlms-systematic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hanzhang Yuan, Mengxuan Hu, Wenhao Zhang, et al.*2026*
57. **[SimpleOCR: Rendering Visual Questions to Teach MLLMs to Read](https://md.research.elamur.ai/free/en/papers/peng-2026-simpleocr-rendering-visual-questions-teach/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yibo Peng, Peng Xia, Ding Zhong, et al.*2026*
58. **[STRUDEL: Unrolling a Benchmark for Evaluating Vision-Language Models on Structured Diagram Understanding across Domains](https://md.research.elamur.ai/free/en/papers/steinigen-2026-strudel-unrolling-benchmark-evaluating-vision/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Daniel Steinigen, Lucie Flek, Sebastian Houben*2026*
59. **[Test-Time Scaling in Multimodal Foundation Models: A Comprehensive Survey of Generation and Reasoning](https://md.research.elamur.ai/free/en/papers/wan-2026-test-time-scaling-multimodal-foundation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Cong Wan, Ying He, Zhongzhan Huang, et al.*2026*
60. **[Towards Scalable Lightweight GUI Agents via Multi-role Orchestration](https://md.research.elamur.ai/free/en/papers/wang-2026-scalable-lightweight-gui-agents-multi/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ziwei Wang, Junjie Zheng, Leyang Yang, et al.*2026*
61. **[VAUQ: Vision-Aware Uncertainty Quantification for LVLM Self-Evaluation](https://md.research.elamur.ai/free/en/papers/park-2026-vauq-vision-aware-uncertainty-quantification/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Seongheon Park, Changdae Oh, Hyeong Kyu Choi, et al.*2026*
62. **[When Seeing Is not Enough: Revealing the Limits of Active Reasoning in MLLMs](https://md.research.elamur.ai/free/en/papers/liu-2026-when-seeing-is-not-enough/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hongcheng Liu, Pingjie Wang, Yuhao Wang, et al.*2026*

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