---
title: "Who cites Faisal Ahmed"
description: "471 papers of the Elamur Research library cite the works of Faisal Ahmed, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/faisal-ahmed/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/faisal-ahmed/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Faisal Ahmed](https://md.research.elamur.ai/free/en/authors/faisal-ahmed/) / cited by

# Who cites Faisal Ahmed

471 citations of their works from 471 papers of our library (of the 140,884 whose bibliographies we read) · 36 with a page here, the most cited first · [← Faisal Ahmed](https://md.research.elamur.ai/free/en/authors/faisal-ahmed/)

1. [**Language Models are Few-Shot Learners**Tom B. Brown, Benjamin Mann, Nick Ryder, et al.*2020 · 10,782 citations*](https://md.research.elamur.ai/free/en/papers/brown-2020-language-models-few-shot-learners/)
2. [**Learning Transferable Visual Models From Natural Language Supervision**Alec Radford, Jong Wook Kim, Chris Hallacy, et al.*2021 · 8,295 citations*](https://md.research.elamur.ai/free/en/papers/radford-2021-learning-transferable-visual-models-natural/)
3. [**BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models**Junnan Li, Dongxu Li, Silvio Savarese, et al.*2023 · 2,114 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-blip-2-bootstrapping-language-image/)
4. [**Flamingo: a Visual Language Model for Few-Shot Learning**Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, et al.*2022 · 2,108 citations*](https://md.research.elamur.ai/free/en/papers/alayrac-2022-flamingo-visual-language-model-few/)
5. [**An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale**Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, et al.*2020 · 1,947 citations*](https://md.research.elamur.ai/free/en/papers/dosovitskiy-2020-image-worth-16x16-words-transformers/)
6. [**Oscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks**Xiujun Li, Xi Yin, Chunyuan Li, et al.*2020 · 1,827 citations*](https://md.research.elamur.ai/free/en/papers/li-2020-oscar-object-semantics-aligned-pre/)
7. [**Pre-trained Models for Natural Language Processing: A Survey**Xipeng Qiu, Tianxiang Sun, Yige Xu, et al.*2020 · 1,740 citations*](https://md.research.elamur.ai/free/en/papers/qiu-2020-pre-trained-models-natural-language/)
8. [**Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision**Chao Jia, Yinfei Yang, Ye Xia, et al.*2021 · 1,528 citations*](https://md.research.elamur.ai/free/en/papers/jia-2021-scaling-up-visual-vision-language/)
9. [**CLIPScore: A Reference-free Evaluation Metric for Image Captioning**Jack Hessel, Ari Holtzman, Maxwell Forbes, et al.*2021 · 1,498 citations*](https://md.research.elamur.ai/free/en/papers/hessel-2021-clipscore-reference-free-evaluation-metric/)
10. [**BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation**Junnan Li, Dongxu Li, Caiming Xiong, et al.*2022 · 1,463 citations*](https://md.research.elamur.ai/free/en/papers/li-2022-blip-bootstrapping-language-image-pre/)
11. [**MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI**Xiang Yue, Yuansheng Ni, Kai Zhang, et al.*2023 · 948 citations*](https://md.research.elamur.ai/free/en/papers/yue-2023-mmmu-massive-multi-discipline-multimodal/)
12. [**Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond**Jinze Bai, Shuai Bai, Shusheng Yang, et al.*2023 · 913 citations*](https://md.research.elamur.ai/free/en/papers/bai-2023-qwen-vl-versatile-vision-language/)
13. [**LayoutLMv3: Pre-training for Document AI with Unified Text and Image Masking**Yupan Huang, Tengchao Lv, Lei Cui, et al.*2022 · 774 citations*](https://md.research.elamur.ai/free/en/papers/huang-2022-layoutlmv3-pre-training-document-ai/)
14. [**ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision**Wonjae Kim, Bokyung Son, Ildoo Kim*2021 · 762 citations*](https://md.research.elamur.ai/free/en/papers/kim-2021-vilt-vision-language-transformer-convolution/)
15. [**CoCa: Contrastive Captioners are Image-Text Foundation Models**Jiahui Yu, Zirui Wang, Vijay Vasudevan, et al.*2022 · 646 citations*](https://md.research.elamur.ai/free/en/papers/yu-2022-coca-contrastive-captioners-image-text/)
16. [**LayoutLMv2: Multi-modal Pre-training for Visually-rich Document Understanding**Yang Xu, Yiheng Xu, Tengchao Lv, et al.*2021 · 623 citations*](https://md.research.elamur.ai/free/en/papers/xu-2021-layoutlmv2-multi-modal-pre-training/)
17. [**SimVLM: Simple Visual Language Model Pretraining with Weak Supervision**Zirui Wang, Jiahui Yu, Adams Wei Yu, et al.*2021 · 459 citations*](https://md.research.elamur.ai/free/en/papers/wang-2021-simvlm-simple-visual-language-model/)
18. [**OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework**Peng Wang, An Yang, Rui Men, et al.*2022 · 452 citations*](https://md.research.elamur.ai/free/en/papers/wang-2022-ofa-unifying-architectures-tasks-modalities/)
19. [**Sequicity: Simplifying Task-oriented Dialogue Systems with Single Sequence-to-Sequence Architectures**Wenqiang Lei, Xisen Jin, Min-Yen Kan, et al.*2018 · 426 citations*](https://md.research.elamur.ai/free/en/papers/lei-2018-sequicity-simplifying-task-oriented-dialogue/)
20. [**Training data-efficient image transformers & distillation through attention**Hugo Touvron, Matthieu Cord, Matthijs Douze, et al.*2020 · 405 citations*](https://md.research.elamur.ai/free/en/papers/touvron-2020-training-data-efficient-image-transformers/)
21. [**PaLI: A Jointly-Scaled Multilingual Language-Image Model**Xi Chen, Xiao Wang, Soravit Changpinyo, et al.*2022 · 339 citations*](https://md.research.elamur.ai/free/en/papers/chen-2022-pali-jointly-scaled-multilingual-language/)
22. [**Visual ChatGPT: Talking, Drawing and Editing with Visual Foundation Models**Chenfei Wu, Shengming Yin, Weizhen Qi, et al.*2023 · 315 citations*](https://md.research.elamur.ai/free/en/papers/wu-2023-visual-chatgpt-talking-drawing-editing/)
23. [**Kosmos-2: Grounding Multimodal Large Language Models to the World**Zhiliang Peng, Wenhui Wang, Li Dong, et al.*2023 · 272 citations*](https://md.research.elamur.ai/free/en/papers/peng-2023-kosmos-2-grounding-multimodal-large/)
24. [**CoSQL: A Conversational Text-to-SQL Challenge Towards Cross-Domain Natural Language Interfaces to Databases**Tao Yu, Rui Zhang, Heyang Er, et al.*2019 · 261 citations*](https://md.research.elamur.ai/free/en/papers/yu-2019-cosql-conversational-text-sql-challenge/)
25. [**SemEval-2022 Task 5: Multimedia Automatic Misogyny Identification**Elisabetta Fersini, Francesca Gasparini, Giulia Rizzi, et al.*2022 · 234 citations*](https://md.research.elamur.ai/free/en/papers/fersini-2022-semeval-2022-task-5-multimedia/)
26. [**Decoupling Strategy and Generation in Negotiation Dialogues**He He, Derek Chen, Anusha Balakrishnan, et al.*2018 · 233 citations*](https://md.research.elamur.ai/free/en/papers/he-2018-decoupling-strategy-generation-negotiation-dialogues/)
27. [**SeamlessM4T: Massively Multilingual & Multimodal Machine Translation**Seamless Communication, Loic Barrault, Yu-An Chung, et al.*2023 · 183 citations*](https://md.research.elamur.ai/free/en/papers/communication-2023-seamlessm4t-massively-multilingual-multimodal-machine/)
28. [**AudioPaLM: A Large Language Model That Can Speak and Listen**Paul K. Rubenstein, Chulayuth Asawaroengchai, Duc Dung Nguyen, et al.*2023 · 169 citations*](https://md.research.elamur.ai/free/en/papers/rubenstein-2023-audiopalm-large-language-model-that/)
29. [**End-to-End Task-Completion Neural Dialogue Systems**Xiujun Li, Yun-Nung Chen, Lihong Li, et al.*2017 · 141 citations*](https://md.research.elamur.ai/free/en/papers/li-2017-end-end-task-completion-neural/)
30. [**What Artificial Neural Networks Can Tell Us About Human Language Acquisition**Alex Warstadt, Samuel R. Bowman*2022 · 72 citations*](https://md.research.elamur.ai/free/en/papers/warstadt-2022-artificial-neural-networks-tell-us/)
31. [**Multimodal Sarcasm Target Identification in Tweets**Jiquan Wang, Lin Sun, Yi Liu, et al.*2022 · 28 citations*](https://md.research.elamur.ai/free/en/papers/wang-2022-multimodal-sarcasm-target-identification-tweets/)
32. [**Bridging the Gap between Synthetic and Authentic Images for Multimodal Machine Translation**Wenyu Guo, Qingkai Fang, Dong Yu, et al.*2023 · 15 citations*](https://md.research.elamur.ai/free/en/papers/guo-2023-bridging-gap-between-synthetic-authentic/)
33. [**Acquiring Linguistic Knowledge from Multimodal Input**Theodor Amariucai, Alexander Scott Warstadt*2023 · 6 citations*](https://md.research.elamur.ai/free/en/papers/amariucai-2023-acquiring-linguistic-knowledge-multimodal-input/)
34. [**GRAVL-BERT: Graphical Visual-Linguistic Representations for Multimodal Coreference Resolution**Danfeng Guo, Arpit Gupta, Sanchit Agarwal, et al.*2022 · 6 citations*](https://md.research.elamur.ai/free/en/papers/guo-2022-gravl-bert-graphical-visual-linguistic/)
35. [**Do Multimodal LLMs Understand Order? Measuring the Fragility of Multimodal Reasoning under Input Order Perturbations**Sheng-Lun Wei, Yu-Ling Liao, Hen-Hsen Huang, et al.*2026*](https://md.research.elamur.ai/free/en/papers/wei-2026-do-multimodal-llms-understand-order/)
36. [**Survey on Vision-language Pre-training (视觉语言预训练综述)**Jiong Yin (殷炯), Zhedong Zhang (张哲东), Yuhan Gao (高宇涵), et al.*2022*](https://md.research.elamur.ai/free/en/papers/yin-2022-vision-language-pre/)

435 more citing papers of our library have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/authors/faisal-ahmed/) — Faisal Ahmed