--- title: "Who cites Hao Fang" description: "496 papers of the Elamur Research library cite the works of Hao Fang, found in their bibliographies · page 1 of 3; the most cited first." canonical: "https://research.elamur.ai/free/en/authors/hao-fang/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/hao-fang/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Hao Fang](https://md.research.elamur.ai/free/en/authors/hao-fang/) / cited by # Who cites Hao Fang 496 citations of their works from 496 papers of our library (of the 140 884 whose bibliographies we read) · 59 with a page here, the most cited first · page 1 of 3 · [← Hao Fang](https://md.research.elamur.ai/free/en/authors/hao-fang/) **1** [2](https://md.research.elamur.ai/free/en/authors/hao-fang/cited-by/page/2/) [3](https://md.research.elamur.ai/free/en/authors/hao-fang/cited-by/page/3/) [next →](https://md.research.elamur.ai/free/en/authors/hao-fang/cited-by/page/2/) - [Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization](https://md.research.elamur.ai/free/en/papers/selvaraju-2016-grad-cam-visual-explanations-deep/) — Ramprasaath R. Selvaraju, Michael Cogswell, Abhishek Das, et al. · 2016 · 6 327 citations - [Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations](https://md.research.elamur.ai/free/en/papers/krishna-2016-visual-genome-connecting-language-vision/) — Ranjay Krishna, Yuke Zhu, Oliver Groth, et al. · 2016 · 5 747 citations - [On the Opportunities and Risks of Foundation Models](https://md.research.elamur.ai/free/en/papers/bommasani-2021-opportunities-risks-foundation-models/) — Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al. · 2021 · 3 044 citations - [ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks](https://md.research.elamur.ai/free/en/papers/lu-2019-vilbert-pretraining-task-agnostic-visiolinguistic/) — Jiasen Lu, Dhruv Batra, Devi Parikh, et al. · 2019 · 2 217 citations - [Flamingo: a Visual Language Model for Few-Shot Learning](https://md.research.elamur.ai/free/en/papers/alayrac-2022-flamingo-visual-language-model-few/) — Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, et al. · 2022 · 2 108 citations - [Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision](https://md.research.elamur.ai/free/en/papers/jia-2021-scaling-up-visual-vision-language/) — Chao Jia, Yinfei Yang, Ye Xia, et al. · 2021 · 1 528 citations - [VisualBERT: A Simple and Performant Baseline for Vision and Language](https://md.research.elamur.ai/free/en/papers/li-2019-visualbert-simple-performant-baseline-vision/) — Liunian Harold Li, Mark Yatskar, Da Yin, et al. · 2019 · 1 510 citations - [Sigmoid Loss for Language Image Pre-Training](https://md.research.elamur.ai/free/en/papers/zhai-2023-sigmoid-loss-language-image-pre/) — Xiaohua Zhai, Basil Mustafa, Alexander Kolesnikov, et al. · 2023 · 1 427 citations - [Vision-and-Language Navigation: Interpreting visually-grounded navigation instructions in real environments](https://md.research.elamur.ai/free/en/papers/anderson-2017-vision-language-navigation-interpreting-visually/) — Peter Anderson, Qi Wu, Damien Teney, et al. · 2017 · 1 346 citations - [Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints](https://md.research.elamur.ai/free/en/papers/zhao-2017-men-also-like-shopping-reducing/) — Jieyu Zhao, Tianlu Wang, Mark Yatskar, et al. · 2017 · 1 030 citations - [VL-BERT: Pre-training of Generic Visual-Linguistic Representations](https://md.research.elamur.ai/free/en/papers/su-2019-vl-bert-pre-training-generic/) — Weijie Su, Xizhou Zhu, Yue Cao, et al. · 2019 · 1 008 citations - [Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond](https://md.research.elamur.ai/free/en/papers/bai-2023-qwen-vl-versatile-vision-language/) — Jinze Bai, Shuai Bai, Shusheng Yang, et al. · 2023 · 913 citations - [Learning to Ask: Neural Question Generation for Reading Comprehension](https://md.research.elamur.ai/free/en/papers/du-2017-learning-ask-neural-question-generation/) — Xinya Du, Junru Shao, Claire Cardie · 2017 · 913 citations - [MMBench: Is Your Multi-modal Model an All-around Player?](https://md.research.elamur.ai/free/en/papers/liu-2023-mmbench-multi-modal-model-all/) — Yuan Liu, Haodong Duan, Yuanhan Zhang, et al. · 2023 · 907 citations - [Learning Distributed Representations of Sentences from Unlabelled Data](https://md.research.elamur.ai/free/en/papers/hill-2016-learning-distributed-representations-sentences-unlabelled/) — Felix Hill, Kyunghyun Cho, Anna Korhonen · 2016 · 756 citations - [CIDEr: Consensus-based Image Description Evaluation](https://md.research.elamur.ai/free/en/papers/vedantam-2014-cider-consensus-based-image-description/) — Ramakrishna Vedantam, C. Lawrence Zitnick, Devi Parikh · 2014 · 733 citations - [Learning To Retrieve Prompts for In-Context Learning](https://md.research.elamur.ai/free/en/papers/rubin-2021-learning-retrieve-prompts-context-learning/) — Ohad Rubin, Jonathan Herzig, Jonathan Berant · 2021 · 717 citations - [CoCa: Contrastive Captioners are Image-Text Foundation Models](https://md.research.elamur.ai/free/en/papers/yu-2022-coca-contrastive-captioners-image-text/) — Jiahui Yu, Zirui Wang, Vijay Vasudevan, et al. · 2022 · 646 citations - [A Corpus for Reasoning About Natural Language Grounded in Photographs (NLVR2)](https://md.research.elamur.ai/free/en/papers/suhr-2019-corpus-reasoning-natural-language-grounded/) — Alane Suhr, Stephanie Zhou, Ally Zhang, et al. · 2019 · 640 citations - [Object Hallucination in Image Captioning](https://md.research.elamur.ai/free/en/papers/rohrbach-2018-object-hallucination-image-captioning/) — Anna Rohrbach, Lisa Anne Hendricks, Kaylee Burns, et al. · 2018 · 617 citations - [How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites](https://md.research.elamur.ai/free/en/papers/chen-2024-far-gpt-4v-closing/) — Zhe Chen, Weiyun Wang, Hao Tian, et al. · 2024 · 529 citations - [MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/fu-2023-mme-comprehensive-evaluation-benchmark-multimodal/) — Chaoyou Fu, Peixian Chen, Yunhang Shen, et al. · 2023 · 529 citations - [Deep Visual-Semantic Alignments for Generating Image Descriptions](https://md.research.elamur.ai/free/en/papers/karpathy-2014-deep-visual-semantic-alignments-generating/) — Andrej Karpathy, Li Fei-Fei · 2014 · 493 citations - [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/) — Dustin Schwenk, Apoorv Khandelwal, Christopher Clark, et al. · 2022 · 490 citations - [SimVLM: Simple Visual Language Model Pretraining with Weak Supervision](https://md.research.elamur.ai/free/en/papers/wang-2021-simvlm-simple-visual-language-model/) — Zirui Wang, Jiahui Yu, Adams Wei Yu, et al. · 2021 · 459 citations **1** [2](https://md.research.elamur.ai/free/en/authors/hao-fang/cited-by/page/2/) [3](https://md.research.elamur.ai/free/en/authors/hao-fang/cited-by/page/3/) [next →](https://md.research.elamur.ai/free/en/authors/hao-fang/cited-by/page/2/)