🔗 Who cites «Vibe-Eval: A hard evaluation suite for measuring progress of multimodal language models»

19 papers of our library cite it (of the 149,439 whose bibliographies we read) · 12 with a page here, the most cited first · ← back to «Vibe-Eval: A hard evaluation suite for measuring progress of multimodal language models»

1. Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic CapabilitiesarXiv:2507.06261Gheorghe Comanici, Eric Bieber, Mike Schaekermann, et al.2025 · 974 citations
2. LLaVA-OneVision: Easy Visual Task TransferarXiv:2408.03326Bo Li, Yuanhan Zhang, Dong Guo, et al.2024 · 477 citations
3. LMMs-Eval: Reality Check on the Evaluation of Large Multimodal ModelsFindings of the Association for Computational LinguisticsKaichen Zhang, Bo Li, Peiyuan Zhang, et al.2025 · 115 citations
4. AudioBench: A Universal Benchmark for Audio Large Language ModelsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Bin Wang, Xunlong Zou, Geyu Lin, et al.2025 · 77 citations
5. MixEval: Deriving Wisdom of the Crowd from LLM Benchmark MixturesConference on Neural Information Processing Systems (NeurIPS)Jinjie Ni, Fuzhao Xue, Xiang Yue, et al.2024 · 47 citations
6. FollowIR: Evaluating and Teaching Information Retrieval Models to Follow InstructionsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Orion Weller, Benjamin Chang, Sean MacAvaney, et al.2025 · 40 citations
7. MiMo-VL Technical ReportarXiv:2506.03569Xiaomi LLM-Core Team, Zihao Yue, Zhenru Lin, et al.2025 · 33 citations
8. Multimodal Needle in a Haystack: Benchmarking Long-Context Capability of Multimodal Large Language ModelsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Hengyi Wang, Haizhou Shi, Shiwei Tan, et al.2025 · 21 citations
9. Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Weihao Xuan, Qingcheng Zeng, Heli Qi, et al.2025 · 11 citations
10. Graders Should Cheat: Privileged Information Enables Expert-Level Automated EvaluationsConference on Empirical Methods in Natural Language Processing (EMNLP)Jin Peng Zhou, Séb Arnold, Nan Ding, et al.2025 · 3 citations
11. VisTW: Benchmarking Vision-Language Models for Taiwanese Mandarin in TaiwanFindings of the Association for Computational LinguisticsZhi Rui Tam, Yung-Yu Shih, Yen-Wei Lee, et al.2026 · 1 citation
12. On the Cultural Anachronism and Temporal Reasoning in Vision Language ModelsFindings of the Association for Computational LinguisticsMukul Ranjan, Prince Jha, Khushboo Kumari, et al.2026

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

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