🧑‍🔬 Who cites Iris Zhang

266 citations of their works from 262 papers of our library (of the 149,439 whose bibliographies we read) · 35 with a page here, the most cited first · ← Iris Zhang

1. LXMERT: Learning Cross-Modality Encoder Representations from TransformersConference on Empirical Methods in Natural Language Processing (EMNLP)Hao Tan, Mohit Bansal2019 · 2,789 citations
2. UNITER: UNiversal Image-TExt Representation LearningLecture notes in computer scienceYen-Chun Chen, Linjie Li, Licheng Yu, et al.2019 · 2,418 citations
3. GQA: A New Dataset for Real-World Visual Reasoning and Compositional Question AnsweringIEEE Computer Society Conference on Computer Vision and Pattern RecognitionDrew A. Hudson, Christopher D. Manning2019 · 2,078 citations
4. Oscar: Object-Semantics Aligned Pre-training for Vision-Language TasksLecture notes in computer scienceXiujun Li, Xi Yin, Chunyuan Li, et al.2020 · 1,877 citations
5. Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language modelsarXiv:2206.04615 · Transactions on Machine Learning Research, May/2022, https://openreview.net/forum?id=uyTL5BvosjAarohi Srivastava, Abhinav Rastogi, Abhishek Rao, et al.2022 · 1,756 citations
6. VisualBERT: A Simple and Performant Baseline for Vision and LanguagearXiv:1908.03557Liunian Harold Li, Mark Yatskar, Da Yin, et al.2019 · 1,568 citations
7. BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and GenerationarXiv:2201.12086Junnan Li, Dongxu Li, Caiming Xiong, et al.2022 · 1,523 citations
8. ViLT: Vision-and-Language Transformer Without Convolution or Region SupervisionarXiv:2102.03334Wonjae Kim, Bokyung Son, Ildoo Kim2021 · 804 citations
9. CoCa: Contrastive Captioners are Image-Text Foundation ModelsarXiv:2205.01917Jiahui Yu, Zirui Wang, Vijay Vasudevan, et al.2022 · 667 citations
10. Evaluating Models' Local Decision Boundaries via Contrast SetsMatt Gardner, Yoav Artzi, Victoria Basmov, et al.2020 · 531 citations
11. TabFact: A Large-scale Dataset for Table-based Fact VerificationarXiv:1909.02164Wenhu Chen, Hongmin Wang, Jianshu Chen, et al.2019 · 515 citations
12. SimVLM: Simple Visual Language Model Pretraining with Weak SupervisionarXiv:2108.10904Zirui Wang, Jiahui Yu, Adams Wei Yu, et al.2021 · 481 citations
13. LLaVA-OneVision: Easy Visual Task TransferarXiv:2408.03326Bo Li, Yuanhan Zhang, Dong Guo, et al.2024 · 477 citations
14. Experience Grounds LanguageConference on Empirical Methods in Natural Language Processing (EMNLP)Yonatan Bisk, Ari Holtzman, Jesse Thomason, et al.2020 · 439 citations
15. The Hateful Memes Challenge: Detecting Hate Speech in Multimodal MemesarXiv:2005.04790Douwe Kiela, Hamed Firooz, Aravind Mohan, et al.2020 · 420 citations
16. Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time ScalingarXiv:2412.05271Zhe Chen, Weiyun Wang, Yue Cao, et al.2024 · 287 citations
17. How Can We Accelerate Progress Towards Human-like Linguistic Generalization?Annual Meeting of the Association for Computational Linguistics (ACL)Tal Linzen2020 · 263 citations
18. Break It Down: A Question Understanding BenchmarkTransactions of the Association for Computational Linguistics (TACL)Tomer Wolfson, Mor Geva, Ankit Gupta, et al.2020 · 222 citations
19. What matters when building vision-language models?Conference on Neural Information Processing Systems (NeurIPS)Hugo Laurençon, Leo Tronchon, Matthieu Cord, et al.2024 · 212 citations
20. Understanding tables with intermediate pre-trainingFindings of the Association for Computational LinguisticsJulian Eisenschlos, Syrine Krichene, Thomas Müller2020 · 158 citations
21. Multimodal Pretraining Unmasked: A Meta-Analysis and a Unified Framework of Vision-and-Language BERTsTransactions of the Association for Computational Linguistics (TACL)Emanuele Bugliarello, Ryan Cotterell, Naoaki Okazaki, et al.2021 · 141 citations
22. SPARTQA: A Textual Question Answering Benchmark for Spatial ReasoningRoshanak Mirzaee, Hossein Rajaby Faghihi, Qiang Ning, et al.2021 · 95 citations
23. MMICL: Empowering Vision-language Model with Multi-Modal In-Context LearningarXiv:2309.07915Haozhe Zhao, Zefan Cai, Shuzheng Si, et al.2023 · 58 citations
24. Decision-Oriented Dialogue for Human-AI CollaborationTransactions of the Association for Computational Linguistics (TACL)Jessy Lin, Nicholas Tomlin, Jacob Andreas, et al.2024 · 57 citations
25. MAmmoTH-VL: Eliciting Multimodal Reasoning with Instruction Tuning at ScaleAnnual Meeting of the Association for Computational Linguistics (ACL)Jiawei Guo, Tianyu Zheng, Yizhi Li, et al.2025 · 40 citations
26. Pragmatics in Language Grounding: Phenomena, Tasks, and Modeling ApproachesFindings of the Association for Computational LinguisticsDaniel Fried, Nicholas Tomlin, Jennifer Hu, et al.2023 · 38 citations
27. New Protocols and Negative Results for Textual Entailment Data CollectionConference on Empirical Methods in Natural Language Processing (EMNLP)Samuel R. Bowman, Jennimaria Palomaki, Livio Baldini Soares, et al.2020 · 27 citations
28. Draw Me a Flower: Processing and Grounding Abstraction in Natural LanguageTransactions of the Association for Computational Linguistics (TACL)Royi Lachmy, Valentina Pyatkin, Avshalom Manevich, et al.2022 · 21 citations
29. Maintaining Common Ground in Dynamic EnvironmentsTransactions of the Association for Computational Linguistics (TACL)Takuma Udagawa, Akiko Aizawa2021 · 13 citations
30. Centurio: On Drivers of Multilingual Ability of Large Vision-Language ModelAnnual Meeting of the Association for Computational Linguistics (ACL)Gregor Geigle, Florian Schneider, Carolin Holtermann, et al.2025 · 9 citations
31. Evaluating Discriminability of Vision-Language ModelsLanguage Resources and Evaluation Conference (LREC)Masayasu Muraoka, Naoaki Okazaki2026
32. Mind's Eye: A Benchmark of Visual Abstraction, Transformation and Composition for Multimodal LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Rohit Sinha, Aditya Sanjiv Kanade, Sai Srinivas Kancheti, et al.2026
33. Multimodal Unlearning Across Vision, Language, Video, and Audio: Survey of Methods, Datasets, and BenchmarksFindings of the Association for Computational LinguisticsNobin Sarwar, Shubhashis Roy Dipta, Zheyuan Liu, et al.2026
34. On the Additive Compositionality of Task Vectors in Vision–Language ModelsConference of the European Chapter of the Association for Computational Linguistics (EACL)Yuting Shi, Houjing Wei, Naoya Inoue2026
35. S2H-DPO: Hardness-Aware Preference Optimization for Vision–Language ModelsFindings of the Association for Computational LinguisticsNitish Shukla, Surgan Jandial, Arun Ross2026

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