--- title: "Who cites Hao Tan — 529 papers of our library" description: "529 papers of the Elamur Research library cite the works of Hao Tan, found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/authors/hao-tan/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/hao-tan/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Hao Tan](https://md.research.elamur.ai/free/en/authors/hao-tan/) / cited by # Who cites Hao Tan 540 citations of their works from 529 papers of our library (of the 141,840 whose bibliographies we read) · 42 with a page here, the most cited first · [← Hao Tan](https://md.research.elamur.ai/free/en/authors/hao-tan/) 1. [**Learning Transferable Visual Models From Natural Language Supervision arXiv:2103.00020**Alec Radford, Jong Wook Kim, Chris Hallacy, et al.*2021 · 8,328 citations*](https://md.research.elamur.ai/free/en/papers/radford-2021-learning-transferable-visual-models-natural/) 2. [**On the Opportunities and Risks of Foundation Models arXiv:2108.07258**Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.*2021 · 3,056 citations*](https://md.research.elamur.ai/free/en/papers/bommasani-2021-opportunities-risks-foundation-models/) **[UNITER: UNiversal Image-TExt Representation Learning](https://md.research.elamur.ai/free/en/papers/chen-2019-uniter-universal-image-text-representation/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Yen-Chun Chen, Linjie Li, Licheng Yu, et al.*2019 · 2,356 citations* [**BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models arXiv:2301.12597**Junnan Li, Dongxu Li, Silvio Savarese, et al.*2023 · 2,122 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-blip-2-bootstrapping-language-image/) **[Oscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks](https://md.research.elamur.ai/free/en/papers/li-2020-oscar-object-semantics-aligned-pre/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Xiujun Li, Xi Yin, Chunyuan Li, et al.*2020 · 1,838 citations* [**Pre-trained Models for Natural Language Processing: A Survey arXiv:2003.08271 · SCIENCE CHINA Technological Sciences,2020, 63, 1872-1897**Xipeng Qiu, Tianxiang Sun, Yige Xu, et al.*2020 · 1,753 citations*](https://md.research.elamur.ai/free/en/papers/qiu-2020-pre-trained-models-natural-language/) [**VL-BERT: Pre-training of Generic Visual-Linguistic Representations arXiv:1908.08530**Weijie Su, Xizhou Zhu, Yue Cao, et al.*2019 · 1,025 citations*](https://md.research.elamur.ai/free/en/papers/su-2019-vl-bert-pre-training-generic/) **[MTEB: Massive Text Embedding Benchmark](https://md.research.elamur.ai/free/en/papers/muennighoff-2022-mteb-massive-text-embedding-benchmark/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Niklas Muennighoff, Nouamane Tazi, Loïc Magne, et al.*2022 · 1,021 citations* **[MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI](https://md.research.elamur.ai/free/en/papers/yue-2023-mmmu-massive-multi-discipline-multimodal/) [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/)**Xiang Yue, Yuansheng Ni, Kai Zhang, et al.*2023 · 948 citations* **[TaPas: Weakly Supervised Table Parsing via Pre-training](https://md.research.elamur.ai/free/en/papers/herzig-2020-tapas-weakly-supervised-table-parsing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jonathan Herzig, Pawel Krzysztof Nowak, Thomas Müller, et al.*2020 · 845 citations* **[LayoutLMv3: Pre-training for Document AI with Unified Text and Image Masking](https://md.research.elamur.ai/free/en/papers/huang-2022-layoutlmv3-pre-training-document-ai/) [ACM International Conference on Multimedia (ACM MM)](https://md.research.elamur.ai/free/en/venues/acm-international-conference-on-multimedia-acm-mm/)**Yupan Huang, Tengchao Lv, Lei Cui, et al.*2022 · 774 citations* [**ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision arXiv:2102.03334**Wonjae Kim, Bokyung Son, Ildoo Kim*2021 · 768 citations*](https://md.research.elamur.ai/free/en/papers/kim-2021-vilt-vision-language-transformer-convolution/) **[ALFRED: A Benchmark for Interpreting Grounded Instructions for Everyday Tasks](https://md.research.elamur.ai/free/en/papers/shridhar-2019-alfred-benchmark-interpreting-grounded-instructions/) [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/)**Mohit Shridhar; Jesse Thomason; Daniel Gordon; Yonatan Bisk; Winson Han; Roozbeh Mottaghi; Luke Zettlemoyer;, Dieter Fox*2019 · 726 citations* [**CoCa: Contrastive Captioners are Image-Text Foundation Models arXiv:2205.01917**Jiahui Yu, Zirui Wang, Vijay Vasudevan, et al.*2022 · 649 citations*](https://md.research.elamur.ai/free/en/papers/yu-2022-coca-contrastive-captioners-image-text/) **[LayoutLMv2: Multi-modal Pre-training for Visually-rich Document Understanding](https://md.research.elamur.ai/free/en/papers/xu-2021-layoutlmv2-multi-modal-pre-training/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yang Xu, Yiheng Xu, Tengchao Lv, et al.*2021 · 623 citations* [**Evaluating Models' Local Decision Boundaries via Contrast Sets**Matt Gardner, Yoav Artzi, Victoria Basmov, et al.*2020 · 522 citations*](https://md.research.elamur.ai/free/en/papers/gardner-2020-evaluating-models-local-decision-boundaries/) **[A-OKVQA: A Benchmark for Visual Question Answering using World Knowledge](https://md.research.elamur.ai/free/en/papers/schwenk-2022-okvqa-benchmark-visual-question-answering/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Dustin Schwenk, Apoorv Khandelwal, Christopher Clark, et al.*2022 · 490 citations* **[HERO: Hierarchical Encoder for Video+Language Omni-representation Pre-training](https://md.research.elamur.ai/free/en/papers/li-2020-hero-hierarchical-encoder-video-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Linjie Li, Yen-Chun Chen, Yu Cheng, et al.*2020 · 468 citations* [**SimVLM: Simple Visual Language Model Pretraining with Weak Supervision arXiv:2108.10904**Zirui Wang, Jiahui Yu, Adams Wei Yu, et al.*2021 · 465 citations*](https://md.research.elamur.ai/free/en/papers/wang-2021-simvlm-simple-visual-language-model/) [**OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework arXiv:2202.03052**Peng Wang, An Yang, Rui Men, et al.*2022 · 455 citations*](https://md.research.elamur.ai/free/en/papers/wang-2022-ofa-unifying-architectures-tasks-modalities/) [**Long Range Arena: A Benchmark for Efficient Transformers arXiv:2011.04006**Yi Tay, Mostafa Dehghani, Samira Abnar, et al.*2020 · 399 citations*](https://md.research.elamur.ai/free/en/papers/tay-2020-long-range-arena-benchmark-efficient/) **[ViperGPT: Visual Inference via Python Execution for Reasoning](https://md.research.elamur.ai/free/en/papers/suris-2023-vipergpt-visual-inference-python-execution/) [IEEE/CVF International Conference on Computer Vision (ICCV)](https://md.research.elamur.ai/free/en/venues/ieee-cvf-international-conference-on-computer-vision-iccv/)**Didac Suris, Sachit Menon, Carl Vondrick*2023 · 354 citations* [**PaLI: A Jointly-Scaled Multilingual Language-Image Model arXiv:2209.06794**Xi Chen, Xiao Wang, Soravit Changpinyo, et al.*2022 · 341 citations*](https://md.research.elamur.ai/free/en/papers/chen-2022-pali-jointly-scaled-multilingual-language/) [**The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision) arXiv:2309.17421**Zhengyuan Yang, Linjie Li, Kevin Lin, et al.*2023 · 304 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-dawn-lmms-preliminary-explorations-gpt/) **[Coreferential Reasoning Learning for Language Representation](https://md.research.elamur.ai/free/en/papers/ye-2020-coreferential-reasoning-learning-language-representation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Deming Ye, Yankai Lin, Jiaju Du, et al.*2020 · 225 citations* [**What Artificial Neural Networks Can Tell Us About Human Language Acquisition arXiv:2208.07998**Alex Warstadt, Samuel R. Bowman*2022 · 176 citations*](https://md.research.elamur.ai/free/en/papers/warstadt-2022-artificial-neural-networks-tell-us/) **[Addressing Semantic Drift in Question Generation for Semi-Supervised Question Answering](https://md.research.elamur.ai/free/en/papers/zhang-2019-addressing-semantic-drift-question-generation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shiyue Zhang, Mohit Bansal*2019 · 174 citations* **[Detecting Harmful Memes and Their Targets](https://md.research.elamur.ai/free/en/papers/pramanick-2021-detecting-harmful-memes-their-targets/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shraman Pramanick, Dimitar Dimitrov, Rituparna Mukherjee, et al.*2021 · 171 citations* **[Chart-to-Text: A Large-Scale Benchmark for Chart Summarization](https://md.research.elamur.ai/free/en/papers/kantharaj-2022-chart-text-large-scale-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shankar Kantharaj, Rixie Tiffany Leong, Xiang Lin, et al.*2022 · 161 citations* [**ERNIE-ViL: Knowledge Enhanced Vision-Language Representations Through Scene Graph arXiv:2006.16934**Fei Yu, Jiji Tang, Weichong Yin, et al.*2020 · 146 citations*](https://md.research.elamur.ai/free/en/papers/yu-2020-ernie-vil-knowledge-enhanced/) **[UniChart: A Universal Vision-language Pretrained Model for Chart Comprehension and Reasoning](https://md.research.elamur.ai/free/en/papers/masry-2023-unichart-universal-vision-language-pretrained/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ahmed Masry, Parsa Kavehzadeh, Xuan Long Do, et al.*2023 · 119 citations* [**Building a Bridge: A Method for Image-Text Sarcasm Detection Without Pretraining on Image-Text Data Proceedings of the First International Workshop on Natural Language Processing Beyond Text**Xinyu Wang, Xiaowen Sun, Tan Yang, et al.*2020 · 62 citations*](https://md.research.elamur.ai/free/en/papers/wang-2020-building-bridge-method-image-text/) **[Pragmatics in Language Grounding: Phenomena, Tasks, and Modeling Approaches](https://md.research.elamur.ai/free/en/papers/fried-2023-pragmatics-language-grounding-phenomena-tasks/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Daniel Fried, Nicholas Tomlin, Jennifer Hu, et al.*2023 · 36 citations* **[Probing Contextual Language Models for Common Ground with Visual Representations](https://md.research.elamur.ai/free/en/papers/ilharco-2021-probing-contextual-language-models-common/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Gabriel Ilharco, Rowan Zellers, Ali Farhadi, et al.*2021 · 32 citations* **[Multimodal Cross-Document Event Coreference Resolution Using Linear Semantic Transfer and Mixed-Modality Ensembles](https://md.research.elamur.ai/free/en/papers/nath-2024-multimodal-cross-document-event-coreference/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Abhijnan Nath, Huma Jamil, Shafiuddin Rehan Ahmed, et al.*2024 · 7 citations* **[Acquiring Linguistic Knowledge from Multimodal Input](https://md.research.elamur.ai/free/en/papers/amariucai-2023-acquiring-linguistic-knowledge-multimodal-input/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Theodor Amariucai, Alexander Scott Warstadt*2023 · 6 citations* **[GRAVL-BERT: Graphical Visual-Linguistic Representations for Multimodal Coreference Resolution](https://md.research.elamur.ai/free/en/papers/guo-2022-gravl-bert-graphical-visual-linguistic/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Danfeng Guo, Arpit Gupta, Sanchit Agarwal, et al.*2022 · 6 citations* [**Language and Planning in Robotic Navigation: A Multilingual Evaluation of State-of-the-Art Models arXiv:2501.05478**Malak Mansour, Ahmed Aly, Bahey Tharwat, et al.*2025 · 2 citations*](https://md.research.elamur.ai/free/en/papers/mansour-2025-language-planning-robotic-navigation-multilingual/) [**Building Common Ground in Dialogue: A Survey Proceedings of the 2nd LUHME Workshop**Tatiana Anikina, Alina Leippert, Simon Ostermann*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/anikina-2025-building-common-ground-dialogue-survey/) **[Do Multimodal LLMs Understand Order? Measuring the Fragility of Multimodal Reasoning under Input Order Perturbations](https://md.research.elamur.ai/free/en/papers/wei-2026-do-multimodal-llms-understand-order/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Sheng-Lun Wei, Yu-Ling Liao, Hen-Hsen Huang, et al.*2026* **[TiC-MuFormer: Time-Aware Caption-Integrated Multimodal Transformers for User-Level Mental Health Modeling](https://md.research.elamur.ai/free/en/papers/tsoumplekas-2026-tic-muformer-time-aware-caption/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Georgios Tsoumplekas, Yannis Spyridis, Vasileios Argyriou*2026* **[Survey on Vision-language Pre-training (视觉语言预训练综述)](https://md.research.elamur.ai/free/en/papers/yin-2022-vision-language-pre/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Jiong Yin (殷炯), Zhedong Zhang (张哲东), Yuhan Gao (高宇涵), et al.*2022* 487 more citing papers of our library have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/authors/hao-tan/) — Hao Tan