---
title: "Who cites EgoSchema: A Diagnostic — 123 citing papers"
description: "123 papers of the Elamur Research library cite «EgoSchema: A Diagnostic Benchmark for Very Long-form Video Language Understanding»…"
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---
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# Who cites «EgoSchema: A Diagnostic Benchmark for Very Long-form Video Language Understanding»

123 papers of our library cite it (of the 149,439 whose bibliographies we read) · 36 with a page here, the most cited first · [← back to «EgoSchema: A Diagnostic Benchmark for Very Long-form Video Language Understanding»](https://md.research.elamur.ai/free/en/papers/mangalam-2023-egoschema-diagnostic-benchmark-very-long/)

1. [**Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context arXiv:2403.05530**Gemini Team, Petko Georgiev, Ving Ian Lei, et al.*2024 · 1,589 citations*](https://md.research.elamur.ai/free/en/papers/gemini-team-2024-gemini-1-5-unlocking-multimodal/)
2. [**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/)
3. [**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/)
4. [**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/)
5. **[MVBench: A Comprehensive Multi-modal Video Understanding Benchmark](https://md.research.elamur.ai/free/en/papers/li-2023-mvbench-comprehensive-multi-modal-video/) [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/)**Kunchang Li, Yali Wang, Yinan He, et al.*2023 · 463 citations*
6. **[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*
7. [**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/)
8. **[InternVideo2: Scaling Foundation Models for Multimodal Video Understanding](https://md.research.elamur.ai/free/en/papers/wang-2024-internvideo2-scaling-foundation-models/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Yi Wang, Kunchang Li, Xinhao Li, et al.*2024 · 253 citations*
9. [**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/)
10. **[Thinking in Space: How Multimodal Large Language Models See, Remember, and Recall Spaces](https://md.research.elamur.ai/free/en/papers/yang-2024-thinking-space-multimodal-large-language/) [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/)**Jihan Yang, Shusheng Yang, Anjali W. Gupta, et al.*2024 · 182 citations*
11. **[LongVideoBench: A Benchmark for Long-context Interleaved Video-Language Understanding](https://md.research.elamur.ai/free/en/papers/wu-2024-longvideobench-benchmark-long-context-interleaved/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Haoning Wu, Dongxu Li, Bei Chen, et al.*2024 · 166 citations*
12. **[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*
13. [**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/)
14. [**VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs arXiv:2406.07476**Zesen Cheng, Sicong Leng, Hang Zhang, et al.*2024 · 118 citations*](https://md.research.elamur.ai/free/en/papers/cheng-2024-videollama-2-advancing-spatial-temporal/)
15. **[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*
16. [**Long Context Transfer from Language to Vision arXiv:2406.16852**Peiyuan Zhang, Kaichen Zhang, Bo Li, et al.*2024 · 73 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-long-context-transfer-language-vision/)
17. [**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/)
18. [**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/)
19. **[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*
20. [**MiMo-VL Technical Report arXiv:2506.03569**Xiaomi LLM-Core Team, Zihao Yue, Zhenru Lin, et al.*2025 · 33 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-llm-mimo-vl-technical-report/)
21. [**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/)
22. [**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/)
23. **[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*
24. **[Shallow Focus, Deep Fixes: Enhancing Shallow Layers Vision Attention Sinks to Alleviate Hallucination in LVLMs](https://md.research.elamur.ai/free/en/papers/zhang-2025-shallow-focus-deep-fixes-enhancing/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xiaofeng Zhang, Yihao Quan, Chen Shen, et al.*2025 · 14 citations*
25. **[Too Many Frames, Not All Useful: Efficient Strategies for Long-Form Video QA](https://md.research.elamur.ai/free/en/papers/park-2026-too-many-frames-not-all/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Jongwoo Park, Kanchana Ranasinghe, Kumara Kahatapitiya, et al.*2026 · 13 citations*
26. **[Audio-centric Video Understanding Benchmark without Text Shortcut](https://md.research.elamur.ai/free/en/papers/yang-2025-audio-centric-video-understanding-benchmark/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yudong Yang, Jimin Zhuang, Guangzhi Sun, et al.*2025 · 10 citations*
27. **[HERMES: KV Cache as Hierarchical Memory for Efficient Streaming Video Understanding](https://md.research.elamur.ai/free/en/papers/zhang-2026-hermes-kv-cache-as-hierarchical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haowei Zhang, Shudong Yang, Jinlan Fu, et al.*2026 · 9 citations*
28. [**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/)
29. **[EgoMemory: Memory-Augmented Personalized Retrieval for Long-Context Egocentric Video](https://md.research.elamur.ai/free/en/papers/tang-2026-egomemory-memory-augmented-personalized-retrieval/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuanmin Tang, Jue Zhang, Xiaoting Qin, et al.*2026*
30. **[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*
31. **[L2Dir: Integrating L2-Norm and Directional Alignment for Unsupervised Contrastive Representation Learning in Multimodal Retrieval](https://md.research.elamur.ai/free/en/papers/zong-2026-l2dir-integrating-l-2-norm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianyu Zong, Rui Dai, Hongzhu Yi, et al.*2026*
32. **[Minimal Clips, Maximum Salience: Long Video Summarization via Key Moment Extraction](https://md.research.elamur.ai/free/en/papers/pennec-2026-minimal-clips-maximum-salience-long/) [International Workshop on Spoken Dialogue System Technology](https://md.research.elamur.ai/free/en/venues/iwsds/)**Galann Pennec, Zhengyuan Liu, Nicholas Asher, et al.*2026*
33. **[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*
34. **[SagaQA: A Multi-hop Reasoning Benchmark for Long-form Narrative Understanding in TV Series](https://md.research.elamur.ai/free/en/papers/pennec-2026-sagaqa-multi-hop-reasoning-benchmark/) [Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)](https://md.research.elamur.ai/free/en/venues/sigdial/)**Galann Pennec, Zhengyuan Liu, Nicholas Asher, et al.*2026*
35. **[Spatiotemporal Sycophancy: Negation-Based Gaslighting in Video Large Language Models](https://md.research.elamur.ai/free/en/papers/tang-2026-spatiotemporal-sycophancy-negation-based-gaslighting/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ziyao Tang, Pengkun Jiao, Bin Zhu, et al.*2026*
36. **[Stop Fixating on Prompts: Reasoning Hijacking and Constraint Tightening for Red-Teaming LLM Agents](https://md.research.elamur.ai/free/en/papers/mao-2026-stop-fixating-prompts-reasoning-hijacking/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yanxu Mao, Peipei Liu, Tiehan Cui, et al.*2026*

87 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/mangalam-2023-egoschema-diagnostic-benchmark-very-long/) — EgoSchema: A Diagnostic Benchmark for Very Long-form Video Language Understanding