---
title: "Who cites Qianyu Chen — 268 papers of our library"
description: "268 papers of the Elamur Research library cite the works of Qianyu Chen, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/qianyu-chen/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/qianyu-chen/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Qianyu Chen](https://md.research.elamur.ai/free/en/authors/qianyu-chen/) / cited by

# Who cites Qianyu Chen

271 citations of their works from 268 papers of our library (of the 149,439 whose bibliographies we read) · 79 with a page here, the most cited first · [← Qianyu Chen](https://md.research.elamur.ai/free/en/authors/qianyu-chen/)

1. [**Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution arXiv:2409.12191**Peng Wang, Shuai Bai, Sinan Tan, et al.*2024 · 860 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-qwen2-vl-enhancing-vision/)
2. **[MM-LLMs: Recent Advances in MultiModal Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2024-mm-llms-recent-advances-multimodal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Duzhen Zhang, Yahan Yu, Jiahua Dong, et al.*2024 · 320 citations*
3. [**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/)
4. [**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/)
5. [**Qwen2.5-Omni Technical Report arXiv:2503.20215**Jin Xu, Zhifang Guo, Jinzheng He, et al.*2025 · 227 citations*](https://md.research.elamur.ai/free/en/papers/xu-2025-qwen2-5-omni-technical/)
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. **[Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models](https://md.research.elamur.ai/free/en/papers/deitke-2024-molmo-pixmo-open-weights-open/) [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/)**Matt Deitke, Christopher Clark, Sangho Lee, et al.*2024 · 216 citations*
8. [**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/)
9. **[LLaVA-CoT: Let Vision Language Models Reason Step-by-Step](https://md.research.elamur.ai/free/en/papers/xu-2024-llava-cot-let-vision-language/) [IEEE/CVF International Conference on Computer Vision (ICCV)](https://md.research.elamur.ai/free/en/venues/ieee-cvf-international-conference-on-computer-vision-iccv/)**Guowei Xu, Peng Jin, Ziang Wu, et al.*2024 · 138 citations*
10. [**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/)
11. [**MMMU-Pro: A More Robust Multi-discipline Multimodal Understanding Benchmark arXiv:2409.02813**Xiang Yue, Tianyu Zheng, Yuansheng Ni, et al.*2024 · 123 citations*](https://md.research.elamur.ai/free/en/papers/yue-2024-mmmu-pro-more-robust-multi/)
12. **[CharXiv: Charting Gaps in Realistic Chart Understanding in Multimodal LLMs](https://md.research.elamur.ai/free/en/papers/wang-2024-charxiv-charting-gaps-realistic-chart/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zirui Wang, Mengzhou Xia, Luxi He, et al.*2024 · 119 citations*
13. **[LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models](https://md.research.elamur.ai/free/en/papers/zhang-2025-lmms-eval-reality-check-evaluation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kaichen Zhang, Bo Li, Peiyuan Zhang, et al.*2025 · 115 citations*
14. [**Multilingual Large Language Model: A Survey of Resources, Taxonomy and Frontiers arXiv:2404.04925**Libo Qin, Qiguang Chen, Yuhang Zhou, et al.*2024 · 75 citations*](https://md.research.elamur.ai/free/en/papers/qin-2024-multilingual-large-language-model-survey/)
15. **[MEGAVERSE: Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks](https://md.research.elamur.ai/free/en/papers/ahuja-2024-megaverse-benchmarking-large-language-models/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Sanchit Ahuja, Divyanshu Aggarwal, Varun Gumma, et al.*2024 · 74 citations*
16. [**JailBreakV: A Benchmark for Assessing the Robustness of MultiModal Large Language Models against Jailbreak Attacks arXiv:2404.03027**Weidi Luo, Siyuan Ma, Xiaogeng Liu, et al.*2024 · 66 citations*](https://md.research.elamur.ai/free/en/papers/luo-2024-jailbreakv-benchmark-assessing-robustness-multimodal/)
17. [**We-Math: Does Your Large Multimodal Model Achieve Human-like Mathematical Reasoning? arXiv:2407.01284**Runqi Qiao, Qiuna Tan, Guanting Dong, et al.*2024 · 65 citations*](https://md.research.elamur.ai/free/en/papers/qiao-2024-math-large-multimodal-model-achieve/)
18. [**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/)
19. [**CogVLM2: Visual Language Models for Image and Video Understanding arXiv:2408.16500**Wenyi Hong, Weihan Wang, Ming Ding, et al.*2024 · 52 citations*](https://md.research.elamur.ai/free/en/papers/hong-2024-cogvlm2-visual-language-models/)
20. **[Stop Looking for “Important Tokens” in Multimodal Language Models: Duplication Matters More](https://md.research.elamur.ai/free/en/papers/wen-2025-stop-looking-important-tokens-multimodal/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zichen Wen, Yifeng Gao, Shaobo Wang, et al.*2025 · 44 citations*
21. [**NVLM: Open Frontier-Class Multimodal LLMs arXiv:2409.11402**Wenliang Dai, Nayeon Lee, Boxin Wang, et al.*2024 · 44 citations*](https://md.research.elamur.ai/free/en/papers/dai-2024-nvlm-open-frontier-class-multimodal/)
22. **[Improve Vision Language Model Chain-of-thought Reasoning](https://md.research.elamur.ai/free/en/papers/zhang-2025-improve-vision-language-model-chain/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruohong Zhang, Bowen Zhang, Yanghao Li, et al.*2025 · 42 citations*
23. **[MAmmoTH-VL: Eliciting Multimodal Reasoning with Instruction Tuning at Scale](https://md.research.elamur.ai/free/en/papers/guo-2025-mammoth-vl-eliciting-multimodal-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiawei Guo, Tianyu Zheng, Yizhi Li, et al.*2025 · 40 citations*
24. **[MinerU2.5: A Decoupled Vision-Language Model for Efficient High-Resolution Document Parsing](https://md.research.elamur.ai/free/en/papers/niu-2026-mineru2-5-decoupled-vision-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junbo Niu, Zheng Liu, Zhuangcheng Gu, et al.*2026 · 35 citations*
25. **[VLSBench: Unveiling Visual Leakage in Multimodal Safety](https://md.research.elamur.ai/free/en/papers/hu-2025-vlsbench-unveiling-visual-leakage-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xuhao Hu, Dongrui Liu, Hao Li, et al.*2025 · 32 citations*
26. [**Baichuan-Omni-1.5 Technical Report arXiv:2501.15368**Yadong Li, Jun Liu, Tao Zhang, et al.*2025 · 28 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-baichuan-omni-1-5/)
27. **[ChartCoder: Advancing Multimodal Large Language Model for Chart-to-Code Generation](https://md.research.elamur.ai/free/en/papers/zhao-2025-chartcoder-advancing-multimodal-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xuanle Zhao, Xianzhen Luo, Qi Shi, et al.*2025 · 24 citations*
28. [**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/)
29. **[ErrorRadar: Benchmarking Complex Mathematical Reasoning of Multimodal Large Language Models Via Error Detection](https://md.research.elamur.ai/free/en/papers/yan-2026-errorradar-benchmarking-complex-mathematical-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yibo Yan, Shen Wang, Jiahao Huo, et al.*2026 · 23 citations*
30. [**MiniCPM4: Ultra-Efficient LLMs on End Devices arXiv:2506.07900**MiniCPM Team, Chaojun Xiao, Yuxuan Li, et al.*2025 · 22 citations*](https://md.research.elamur.ai/free/en/papers/minicpm-team-2025-minicpm4-ultra-efficient-llms/)
31. [**MMSci: A Dataset for Graduate-Level Multi-Discipline Multimodal Scientific Understanding arXiv:2407.04903**Zekun Li, Xianjun Yang, Kyuri Choi, et al.*2024 · 20 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-mmsci-dataset-graduate-level-multi/)
32. [**Baichuan-Omni Technical Report arXiv:2410.08565**Yadong Li, Haoze Sun, Mingan Lin, et al.*2024 · 18 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-baichuan-omni-technical-report/)
33. [**Baichuan-Audio: A Unified Framework for End-to-End Speech Interaction arXiv:2502.17239**Tianpeng Li, Jun Liu, Tao Zhang, et al.*2025 · 16 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-baichuan-audio-unified-framework/)
34. [**Infinity-MM: Scaling Multimodal Performance with Large-Scale and High-Quality Instruction Data arXiv:2410.18558**Shuhao Gu, Jialing Zhang, Siyuan Zhou, et al.*2024 · 13 citations*](https://md.research.elamur.ai/free/en/papers/gu-2024-infinity-mm-scaling-multimodal-performance/)
35. **[SoundMind: RL-Incentivized Logic Reasoning for Audio-Language Models](https://md.research.elamur.ai/free/en/papers/diao-2025-soundmind-rl-incentivized-logic-reasoning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xingjian Diao, Chunhui Zhang, Keyi Kong, et al.*2025 · 11 citations*
36. [**GAOKAO-MM: A Chinese Human-Level Benchmark for Multimodal Models Evaluation arXiv:2402.15745**Yi Zong, Xipeng Qiu*2024 · 11 citations*](https://md.research.elamur.ai/free/en/papers/zong-2024-gaokao-mm-chinese-human/)
37. **[Centurio: On Drivers of Multilingual Ability of Large Vision-Language Model](https://md.research.elamur.ai/free/en/papers/geigle-2025-centurio-drivers-multilingual-ability-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Gregor Geigle, Florian Schneider, Carolin Holtermann, et al.*2025 · 9 citations*
38. **[TriFine: A Large-Scale Dataset of Vision-Audio-Subtitle for Tri-Modal Machine Translation and Benchmark with Fine-Grained Annotated Tags](https://md.research.elamur.ai/free/en/papers/guan-2025-trifine-large-scale-dataset-vision/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Boyu Guan, Yining Zhang, Yang Zhao, et al.*2025 · 9 citations*
39. **[Autoregressive Semantic Visual Reconstruction Helps VLMs Understand Better](https://md.research.elamur.ai/free/en/papers/wang-2026-autoregressive-semantic-visual-reconstruction-helps/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Dianyi Wang, Wei Song, Yikun Wang, et al.*2026 · 7 citations*
40. **[Doc-React: Multi-page Heterogeneous Document Question-answering](https://md.research.elamur.ai/free/en/papers/wu-2025-doc-react-multi-page-heterogeneous/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junda Wu, Yu Xia, Tong Yu, et al.*2025 · 6 citations*
41. [**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/)
42. **[LAD-RAG: Layout-aware Dynamic RAG for Visually-Rich Document Understanding](https://md.research.elamur.ai/free/en/papers/sourati-2026-lad-rag-layout-aware-dynamic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhivar Sourati, Zheng Wang, Marianne Menglin Liu, et al.*2026 · 4 citations*
43. **[Closing the Modality Reasoning Gap for Speech Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-closing-modality-reasoning-gap-speech/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chaoren Wang, Heng Lu, Xueyao Zhang, et al.*2026 · 2 citations*
44. **[GM-PRM: A Generative Multimodal Process Reward Model for Multimodal Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/zhang-2026-gm-prm-generative-multimodal-process/) [Workshop on Advances in Language and Vision Research (ALVR)](https://md.research.elamur.ai/free/en/venues/alvr/)**Jianghangfan Zhang, Yibo Yan, Kening Zheng, et al.*2026 · 2 citations*
45. **[MERLIN: A Testbed for Multilingual Multimodal Entity Recognition and Linking](https://md.research.elamur.ai/free/en/papers/ramamoorthy-2026-merlin-testbed-multilingual-multimodal-entity/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Sathyanarayanan Ramamoorthy, Vishwa Shah, Simran Khanuja, et al.*2026 · 2 citations*
46. **[TechING: Towards Real World Technical Image Understanding via VLMs](https://md.research.elamur.ai/free/en/papers/nadeem-2026-teching-real-world-technical-image/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tafazzul Nadeem, Bhavik Shangari, Manish Rai, et al.*2026 · 2 citations*
47. **[DART: Leveraging Multi-Agent Disagreement for Tool Recruitment in Multimodal Reasoning](https://md.research.elamur.ai/free/en/papers/sivakumaran-2026-dart-leveraging-multi-agent-disagreement/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Nithin Sivakumaran, Justin Chen, David Wan, et al.*2026 · 1 citation*
48. **[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*
49. **[SEE: Signal Embedding Energy for Quantifying Noise Interference in Large Audio Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-see-signal-embedding-energy-quantifying/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuanhe Zhang, Jiayu Tian, Yibo Zhang, et al.*2026 · 1 citation*
50. **[SPD-Faith Bench: Diagnosing and Improving Faithfulness in Chain-of-Thought for Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/lv-2026-spd-faith-bench-diagnosing-improving/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Weijiang Lv, Yaoxuan Feng, Xiaobo Xia, et al.*2026 · 1 citation*
51. **[UltraEval-Audio: A Unified Framework for Comprehensive Evaluation of Audio Foundation Models](https://md.research.elamur.ai/free/en/papers/shi-2026-ultraeval-audio-unified-framework-comprehensive/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qundong Shi, Jie Zhou, Biyuan Lin, et al.*2026 · 1 citation*
52. **[USB: A COMPREHENSIVE AND UNIFIED SAFETY EVALUATION BENCHMARK FOR MULTIMODAL LARGE LANGUAGE MODELS](https://md.research.elamur.ai/free/en/papers/zheng-2026-usb-comprehensive-unified-safety-evaluation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Baolin Zheng, Guanlin Chen, Qingyang Teng, et al.*2026 · 1 citation*
53. **[When Helpers Become Hazards: A Benchmark for Analyzing Multimodal LLM-Powered Safety in Daily Life](https://md.research.elamur.ai/free/en/papers/lou-2026-when-helpers-become-hazards-benchmark/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xinyue Lou, Xu Jinan, Jingyi Yin, et al.*2026 · 1 citation*
54. **[BitMar: Low-Bit Multimodal Fusion with Episodic Memory for Edge Devices](https://md.research.elamur.ai/free/en/papers/aman-2025-bitmar-low-bit-multimodal-fusion/) [BabyLM Workshop](https://md.research.elamur.ai/free/en/venues/babylm/)**Euhid Aman, Esteban Carlin, Hsing-Kuo Kenneth Pao, et al.*2025 · 1 citation*
55. [**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/)
56. **[A Multistage Extraction Pipeline for Long Scanned Financial Documents: An Empirical Study in Industrial KYC Workflows](https://md.research.elamur.ai/free/en/papers/yuxuan-2026-multistage-extraction-pipeline-long-scanned/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Han Yuxuan, Yuanxing Zhang, Yushuo Wang, et al.*2026*
57. **[AICA-Bench: Holistically Examining the Capabilities of VLMs in Affective Image Content Analysis](https://md.research.elamur.ai/free/en/papers/she-2026-aica-bench-holistically-examining-capabilities/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Dong She, Xianrong Yao, Liqun Chen, et al.*2026*
58. **[Benchmarking Deflection and Hallucination in Large Vision-Language Models](https://md.research.elamur.ai/free/en/papers/moratelli-2026-benchmarking-deflection-hallucination-large-vision/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nicholas Moratelli, Christopher Davis, Leonardo F. R. Ribeiro, et al.*2026*
59. **[Beyond Modality Collapse: Taming Guided Modality Entropy for Omni-modal Emotion Reasoning](https://md.research.elamur.ai/free/en/papers/zhao-2026-beyond-modality-collapse-taming-guided/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xian Zhao, Rui Hu, Yuxiang Zhang, et al.*2026*
60. **[Chart-MRAG: Benchmarking Multimodal Retrieval Augmented Generation on Chart-based Documents](https://md.research.elamur.ai/free/en/papers/ymyang-2026-chart-mrag-benchmarking-multimodal-retrieval/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ymyang, Jiang Zhong, Li Jin, et al.*2026*
61. **[Enhancing Multimodal Large Language Models for Ancient Chinese Character Evolution Analysis via Glyph-Driven Fine-Tuning](https://md.research.elamur.ai/free/en/papers/song-2026-enhancing-multimodal-large-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rui Song, Lida Shi, Ruihua Qi, et al.*2026*
62. [**Harm or Humor: A Multimodal, Multilingual Benchmark for Overt and Covert Harmful Humor arXiv:2603.17759**Ahmed Sharshar, Hosam Elgendy, Saad El Dine Ahmed, et al.*2026*](https://md.research.elamur.ai/free/en/papers/sharshar-2026-harm-humor-multimodal-multilingual-benchmark/)
63. **[HearSay Benchmark: Do Audio LLMs Leak What They Hear?](https://md.research.elamur.ai/free/en/papers/wang-2026-hearsay-benchmark-do-audio-llms/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jin Wang, Kaiwen Luo, Liang Lin, et al.*2026*
64. **[HowToNarrate: A General-Domain Benchmark for Synchronized Video Narration with External Knowledge](https://md.research.elamur.ai/free/en/papers/wang-2026-howtonarrate-general-domain-benchmark-synchronized/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xueyan Wang, Dingyi Yang, Qin Jin*2026*
65. **[Lang2Act: Fine-Grained Visual Reasoning through Self-Emergent Linguistic Toolchains](https://md.research.elamur.ai/free/en/papers/xiong-2026-lang2act-fine-grained-visual-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuqi Xiong, Chunyi Peng, Zhipeng Xu, et al.*2026*
66. **[MirrorQA: Benchmarking Multimodal LLMs on Mirror-Orientation Reasoning](https://md.research.elamur.ai/free/en/papers/liu-2026-mirrorqa-benchmarking-multimodal-llms-mirror/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingping Liu, Xingchen Peng, Yan Zhou, et al.*2026*
67. **[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*
68. **[M³-VQA: A Benchmark for Multimodal, Multi-Entity, Multi-Hop Visual Question Answering](https://md.research.elamur.ai/free/en/papers/ma-2026-m-3-vqa-benchmark-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiatong Ma, Longteng Guo, Yuchen Liu, et al.*2026*
69. **[New Compendium of a Myriad of Plants: A New Dataset Describing Ancient Chinese Plants](https://md.research.elamur.ai/free/en/papers/shen-2026-new-compendium-myriad-plants-new/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiaobin Shen, Zhongqing Wang, Shichen Li, et al.*2026*
70. **[RealTalk-CN: A Realistic Chinese Speech Task-Oriented Dialogue Benchmark with Cross-Modal Analysis](https://md.research.elamur.ai/free/en/papers/wang-2026-realtalk-cn-realistic-chinese-speech/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Enzhi Wang, Jiaming Zhou, Yuhang Jia, et al.*2026*
71. **[ROMA: Real-time Omni-Multimodal Assistant with Interactive Streaming Understanding](https://md.research.elamur.ai/free/en/papers/xueyun-2026-roma-real-time-omni-multimodal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tian Xueyun, Wei Li, Bingbing Xu, et al.*2026*
72. **[Router-Suggest: Dynamic Routing for Multimodal Auto-Completion in Visually-Grounded Dialogs](https://md.research.elamur.ai/free/en/papers/mishra-2026-router-suggest-dynamic-routing-multimodal/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Sandeep Mishra, Devichand Budagam, Anubhab Mandal, et al.*2026*
73. **[RSA-Bench: Benchmarking Audio Large Models in Real-World Acoustic Scenarios](https://md.research.elamur.ai/free/en/papers/zhang-2026-rsa-bench-benchmarking-audio-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yibo Zhang, Kaiwen Luo, Liang Lin, et al.*2026*
74. **[Seeing the Other Side: Diagnostic Tasks for Viewpoint Reasoning in Vision–Language Models](https://md.research.elamur.ai/free/en/papers/takenaka-2026-seeing-other-side-diagnostic-tasks/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Makoto Takenaka, Hitomi Yanaka*2026*
75. **[SMILE-Next: Teaching Large Language Models to Detect, Classify, and Reason about Laughter](https://md.research.elamur.ai/free/en/papers/mok-2026-smile-next-teaching-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lee Jung-Mok, Kim Sung-Bin, Joohyun Chang, et al.*2026*
76. **[The Challenge of Identifying the Origin of Black-Box Large Language Models](https://md.research.elamur.ai/free/en/papers/yang-2026-challenge-identifying-origin-black-box/) [Workshop on Privacy in Natural Language Processing](https://md.research.elamur.ai/free/en/venues/privatenlp/)**Ziqing Yang, Yixin Wu, Yun Shen, et al.*2026*
77. **[Unveiling Inherent Visual Grounding in Multimodal LLMs for Text-Rich Images](https://md.research.elamur.ai/free/en/papers/zhou-2026-unveiling-inherent-visual-grounding-multimodal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shijie Zhou, Jihyung Kil, Ming Li, et al.*2026*
78. **[v-HUB: A Benchmark for Video Humor Understanding from Vision and Sound](https://md.research.elamur.ai/free/en/papers/shi-2026-v-hub-benchmark-video-humor/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhengpeng Shi, Yanpeng Zhao, Jianqun Zhou, et al.*2026*
79. **[ViX-Ray: A Vietnamese Chest X-Ray Dataset for Vision-Language Models](https://md.research.elamur.ai/free/en/papers/nguyen-2026-vix-ray-vietnamese-chest-x/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Duy Vu Minh Nguyen, Chinh Thanh Truong, Trần Hoàng Phúc, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/authors/qianyu-chen/) — Qianyu Chen