KAT: A Knowledge Augmented Transformer for Vision-and-Language

Deep Residual Learning for Image Recognition

He, K., Zhang, X., Ren, S., & Sun, J. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.90 · Cited by 235,474 · see citing works

Attention Is All You Need

Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, L., & Polosukhin, I. (2017) · arXiv · doi:10.48550/arxiv.1706.03762 · Cited by 120,404 · see citing works

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

Ren, S., He, K., Girshick, R., & Sun, J. (2017) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2016.2577031 · Cited by 56,035 · see citing works

Language Models are Few-Shot Learners

Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al. (2020) · arXiv · doi:10.48550/arxiv.2005.14165 · Cited by 23,372 · see citing works

Learning Transferable Visual Models From Natural Language Supervision

Radford, A., Kim, J. W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al. (2021) · arXiv · doi:10.48550/arxiv.2103.00020 · Cited by 15,293 · see citing works

Decoupled Weight Decay Regularization

Loshchilov, I., & Hutter, F. (2017) · arXiv · doi:10.48550/arxiv.1711.05101 · Cited by 12,522 · see citing works

Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

Raffel, C., Shazeer, N., Roberts, A., Lee, K., Narang, S., Matena, M., Zhou, Y., Li, W., & Liu, P. J. (2019) · arXiv · doi:10.48550/arxiv.1910.10683 · Cited by 10,929 · see citing works

BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension

Lewis, M., Liu, Y., Goyal, N., Ghazvininejad, M., Mohamed, A., Levy, O., Stoyanov, V., & Zettlemoyer, L. (2020) · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics · doi:10.18653/v1/2020.acl-main.703 · Cited by 8,821 · see citing works

DBpedia: A Nucleus for a Web of Open Data

Auer, S., Bizer, C., Kobilarov, G., Lehmann, J., Richard Cyganiak, A., & Ives, Z. G. (2007) · Lecture notes in computer science · doi:10.1007/978-3-540-76298-0_52 · Cited by 4,847 · see citing works

Billion-scale similarity search with GPUs

Johnson, J., Douze, M., & Jegou, H. (2021) · IEEE Transactions on Big Data · doi:10.1109/tbdata.2019.2921572 · Cited by 4,228 · see citing works

Dense passage retrieval for open-domain question answering

Karpukhin, V., Oguz, B., Min, S., Lewis, P., Wu, L., Edunov, S., Chen, D., & Yih, W.-T. (2020) · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2020.emnlp-main.550 · Cited by 3,575 · see citing works

Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

Lewis, P., Perez, E., Piktus, A., Petroni, F., Karpukhin, V., Goyal, N., Küttler, H., Lewis, M., Yih, W.-T., Rocktäschel, T., et al. (2020) · arXiv · doi:10.48550/arxiv.2005.11401 · Cited by 3,101 · see citing works

LXMERT: Learning Cross-Modality Encoder Representations from Transformers

Tan, H., & Bansal, M. (2019) · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) · doi:10.18653/v1/d19-1514 · Cited by 2,319 · see citing works

ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks

Lu, J., Batra, D., Parikh, D., & Lee, S. (2019) · arXiv · doi:10.48550/arxiv.1908.02265 · Cited by 2,109 · see citing works

Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Jia, C., Yang, Y., Xia, Y., Chen, Y.-T., Parekh, Z., Pham, H., Le, Q. V., Sung, Y., Li, Z., & Duerig, T. (2021) · arXiv · doi:10.48550/arxiv.2102.05918 · Cited by 1,977 · see citing works

Oscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks

Li, X., Yin, X. P., Li, C., Zhang, P., Hu, X., Zhang, L., Wang, L., Hu, H., Li, D., Wei, F., et al. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-58577-8_8 · Cited by 1,736 · see citing works

ConceptNet — A Practical Commonsense Reasoning Tool-Kit

Liu, H., & Singh, P. K. (2004) · BT Technology Journal · doi:10.1023/b:bttj.0000047600.45421.6d · Cited by 1,592 · see citing works

Reading Wikipedia to answer open-domain questions

Chen, D., Fisch, A., Weston, J., & Bordes, A. (2017) · Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · doi:10.18653/v1/p17-1171 · Cited by 1,546 · see citing works

VisualBERT: A Simple and Performant Baseline for Vision and Language

Li, L. H., Yatskar, M., Yin, D., Hsieh, C.-J., & Chang, K.-W. (2019) · arXiv · doi:10.48550/arxiv.1908.03557 · Cited by 1,198 · see citing works

Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering

Izacard, G., & Grave, E. (2021) · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume · doi:10.18653/v1/2021.eacl-main.74 · Cited by 1,109 · see citing works

VL-BERT: Pre-training of Generic Visual-Linguistic Representations

Su, W., Zhu, X., Cao, Y., Li, B., Lu, L., Wei, F., & Dai, J. (2019) · arXiv · doi:10.48550/arxiv.1908.08530 · Cited by 950 · see citing works

Unicoder-VL: A Universal Encoder for Vision and Language by Cross-Modal Pre-Training

Li, G., Duan, N., Fang, Y., Gong, M., & Jiang, D. (2020) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v34i07.6795 · Cited by 795 · see citing works

Latent retrieval for weakly supervised open domain question answering

Lee, K., Chang, M.-W., & Toutanova, K. (2019) · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics · doi:10.18653/v1/p19-1612 · Cited by 771 · see citing works

OK-VQA: A Visual Question Answering Benchmark Requiring External Knowledge

Marino, K., Rastegari, M., Farhadi, A., & Mottaghi, R. (2019) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2019.00331 · Cited by 749 · see citing works

VQA: Visual Question Answering: www.visualqa.org

Agrawal, A., Lu, J., Antol, S., Mitchell, M., Zitnick, C. L., Parikh, D., & Batra, D. (2017) · International Journal of Computer Vision · doi:10.1007/s11263-016-0966-6 · Cited by 570 · see citing works

FVQA: Fact-Based Visual Question Answering

Wang, P., Wu, Q., Shen, C., Dick, A., & van den Hengel, A. (2017) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2017.2754246 · Cited by 490 · see citing works

An Empirical Study of GPT-3 for Few-Shot Knowledge-Based VQA

Yang, Z., Gan, Z., Wang, J., Hu, X., Lu, Y., Liu, Z., & Wang, L. (2022) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v36i3.20215 · Cited by 334 · see citing works

Explicit Knowledge-based Reasoning for Visual Question Answering

Wang, P., Wu, Q., Shen, C., Dick, A., & van den Hengel, A. (2017) · International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2017/179 · Cited by 240 · see citing works

KRISP: Integrating Implicit and Symbolic Knowledge for Open-Domain Knowledge-Based VQA

Marino, K., Chen, X., Parikh, D., Gupta, A., & Rohrbach, M. (2021) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr46437.2021.01389 · Cited by 204 · see citing works

Out of the Box: Reasoning with Graph Convolution Nets for Factual Visual Question AnsweringPreprint

Narasimhan, M., Lazebnik, S., & Schwing, A. G. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1811.00538 · Cited by 184 · see citing works

Symbolic Knowledge Distillation: from General Language Models to Commonsense Models

West, P., Bhagavatula, C., Hessel, J., Hwang, J. D., Jiang, L., Bras, R. J. L., Lu, X., Welleck, S., & Choi, Y. (2022) · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · doi:10.18653/v1/2022.naacl-main.341 · Cited by 165 · see citing works

ConceptBert: Concept-Aware Representation for Visual Question Answering

Gardères, F., Ziaeefard, M., Abeloos, B., & Lécué, F. (2020) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2020.findings-emnlp.44 · Cited by 151 · see citing works

Multi-Modal Answer Validation for Knowledge-Based VQA

Wu, J., Lu, J., Sabharwal, A., & Mottaghi, R. (2022) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v36i3.20174 · Cited by 141 · see citing works

Boosting Visual Question Answering with Context-aware Knowledge Aggregation

Li, G., Wang, X. Y., & Zhu, W. (2020) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3394171.3413943 · Cited by 86 · see citing works

Weakly-Supervised Visual-Retriever-Reader for Knowledge-based Question Answering

Luo, M., Zeng, Y., Banerjee, P., & Baral, C. R. (2021) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2021.emnlp-main.517 · Cited by 67 · see citing works

KB-VLP: Knowledge Based Vision and Language Pretraining

Chen, K., Huang, Q., Bisk, Y., McDuff, D., & Gao, J. (2021) · International Conference on Machine Learning · Cited by 6 · see citing works

NICE: Neural Image Commenting with Empathy

Chen, K., Huang, Q., McDuff, D., Gao, X., Palangi, H., Wang, J., Forbus, K. D., & Gao, J. (2021) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2021.findings-emnlp.380 · Cited by 5 · see citing works

Learning Inference Rules with Neural TP-Reasoner

Chen, K., Huang, Q., Smolensky, P., Forbus, K. D., & Gao, J. (2020) · Cited by 1 · see citing works

Flamingo: a visual language model for few-shot learning

Alayrac, J.-B., Donahue, J., Luc, P., Miech, A., Barr, I., Hasson, Y., Lenc, K., Mensch, A., Millican, K., Reynolds, M., et al. (2022) · Advances in Neural Information Processing Systems 35 · doi:10.52202/068431-1723 · Cited by 966 · see citing works

A Survey of GPT-3 Family Large Language Models Including ChatGPT and GPT-4

Kalyan, K. S. (2024) · Natural Language Processing Journal · doi:10.1016/j.nlp.2023.100048 · Cited by 335 · see citing works

ViperGPT: Visual Inference via Python Execution for Reasoning

Surís, D., Menon, S., & Vondrick, C. (2023) · 2023 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.01092 · Cited by 273 · see citing works

Prompting Large Language Models with Answer Heuristics for Knowledge-Based Visual Question Answering

Shao, Z., Zhou, Y., Wang, M., & Yu, J. (2023) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52729.2023.01438 · Cited by 232 · see citing works

Vision-Language Pre-Training: Basics, Recent Advances, and Future Trends

Gan, Z., Li, L., Li, C., Wang, L., Liu, Z., & Gao, J. (2022) · Foundations and Trends® in Computer Graphics and Vision · doi:10.1561/0600000105 · Cited by 155 · see citing works

From Images to Textual Prompts: Zero-shot Visual Question Answering with Frozen Large Language Models

Guo, J., Li, J., Li, D., Tiong, A. M. H., Li, B., Tao, D., & Hoi, S. C. H. (2023) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52729.2023.01046 · Cited by 164 · see citing works

Multimodal Foundation Models: From Specialists to General-Purpose Assistants

Li, C., Gan, Z., Yang, Z., Yang, J., Li, L., Wang, L., & Gao, J. (2024) · Foundations and Trends® in Computer Graphics and Vision · doi:10.1561/0600000110 · Cited by 225 · see citing works

Transform-Retrieve-Generate: Natural Language-Centric Outside-Knowledge Visual Question Answering

Gao, F., Ping, Q., Thattai, G., Reganti, A., Wu, Y. N., & Natarajan, P. (2022) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52688.2022.00501 · Cited by 105 · see citing works

Reveal: Retrieval-Augmented Visual-Language Pre-Training with Multi-Source Multimodal Knowledge Memory

Hu, Z., İşcen, A., Sun, C., Wang, Z., Chang, K.-W., Sun, Y., Schmid, C., Ross, D. A., & Fathi, A. (2023) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52729.2023.02238 · Cited by 96 · see citing works

Prompting for Multimodal Hateful Meme Classification

Cao, R., Lee, R. K.-W., Chong, W.-H., & Jiang, J. (2022) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2022.emnlp-main.22 · Cited by 101 · see citing works

PromptCap: Prompt-Guided Image Captioning for VQA with GPT-3

Hu, Y., Hua, H., Yang, Z., Shi, W., Smith, N. A., & Luo, J. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.00277 · Cited by 136 · see citing works

Knowledge Graphs for Multi-modal Learning: Survey and Perspective

Chen, Z., Zhang, Y., Fang, Y., Geng, Y., Guo, L., Chen, J., Liu, X., Pan, J. Z., Zhang, N., Chen, H., et al. (2025) · Information Fusion · doi:10.1016/j.inffus.2025.103124 · Cited by 72 · see citing works

R-VQA: A robust visual question answering model

Chowdhury, S., & Soni, B. (2024) · Knowledge-Based Systems · doi:10.1016/j.knosys.2024.112827 · Cited by 67 · see citing works

Retrieving Multimodal Information for Augmented Generation: A Survey

Zhao, R., Chen, H., Wang, W., Jiao, F., Long, X., Qin, C., Ding, B., Guo, X., Li, M., Li, X., et al. (2023) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2023.findings-emnlp.314 · Cited by 66 · see citing works

Retrieval Augmented Visual Question Answering with Outside Knowledge

Lin, W., & Byrne, B. (2022) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2022.emnlp-main.772 · Cited by 85 · see citing works

LAVIS: A One-stop Library for Language-Vision Intelligence

Li, D., Li, J., Le, H., Wang, G., Savarese, S., & Hoi, S. C. H. (2023) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2023.acl-demo.3 · Cited by 61 · see citing works

Can Pre-trained Vision and Language Models Answer Visual Information-Seeking Questions?

Chen, Y., Hu, H., Luan, Y., Sun, H., Changpinyo, S., Ritter, A., & Chang, M.-W. (2023) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2023.emnlp-main.925 · Cited by 78 · see citing works

VLC-BERT: Visual Question Answering with Contextualized Commonsense Knowledge

Ravi, S., Chinchure, A., Sigal, L., Liao, R., & Shwartz, V. (2023) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv56688.2023.00121 · Cited by 49 · see citing works

Visual Chain-of-Thought Prompting for Knowledge-Based Visual Reasoning

Chen, Z., Zhou, Q., Shen, Y., Hong, Y., Sun, Z., Gutfreund, D., & Gan, C. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v38i2.27888 · Cited by 48 · see citing works

A knowledge-enhanced network for joint multimodal entity-relation extraction

Huang, S., Cai, Y., Yuan, L., & Wang, J. (2024) · Information Processing & Management · doi:10.1016/j.ipm.2024.104033 · Cited by 38 · see citing works

Encyclopedic VQA: Visual questions about detailed properties of fine-grained categories

Mensink, T., Uijlings, J., Castrejón, L., Goel, A., Cadar, F., Zhou, H., Sha, F., Araújo, A. D. M., & Ferrari, V. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.00289 · Cited by 35 · see citing works

Explainable Knowledge reasoning via thought chains for knowledge-based visual question answering

Qiu, C., Xie, Z., Liu, M., & Hu, H. (2024) · Information Processing & Management · doi:10.1016/j.ipm.2024.103726 · Cited by 33 · see citing works

Candidate-Heuristic In-Context Learning: A new framework for enhancing medical visual question answering with LLMs

Xiao, L., Wang, D., Zhong, H., Wang, Q., Li, R., Jia, R., & Wan, B. (2024) · Information Processing & Management · doi:10.1016/j.ipm.2024.103805 · Cited by 32 · see citing works

Knowledge-Aware Text–Image Retrieval for Remote Sensing Images

Li, M., Dai, X., Castillo-Navarro, J., & Tuia, D. (2024) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2024.3486977 · Cited by 33 · see citing works

LaKo: Knowledge-driven Visual Question Answering via Late Knowledge-to-Text Injection

Chen, Z., Huang, Y., Chen, J., Geng, Y., Yin, F., Pan, J. Z., Zhang, N., & Zhang, W. (2022) · International Joint Conference on Knowledge Graphs (IJCKG) · doi:10.1145/3579051.3579053 · Cited by 32 · see citing works

ZVQAF: Zero-shot visual question answering with feedback from large language models

Liu, C., Wang, C., Peng, Y., & Li, Z. (2024) · Neurocomputing · doi:10.1016/j.neucom.2024.127505 · Cited by 29 · see citing works

Improving deep learning with prior knowledge and cognitive models: A survey on enhancing explainability, adversarial robustness and zero-shot learning

Mumuni, F., & Mumuni, A. (2023) · Cognitive Systems Research · doi:10.1016/j.cogsys.2023.101188 · Cited by 28 · see citing works

A Symmetric Dual Encoding Dense Retrieval Framework for Knowledge-Intensive Visual Question Answering

Salemi, A., Pizzorno, J. A., & Zamani, H. (2023) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3539618.3591629 · Cited by 27 · see citing works

What Makes Multimodal In-Context Learning Work?

Baldassini, F. B., Shukor, M., Cord, M., Soulier, L., & Piwowarski, B. (2024) · 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw63382.2024.00161 · Cited by 75 · see citing works

Prophet: Prompting Large Language Models With Complementary Answer Heuristics for Knowledge-Based Visual Question Answering

Zhou, Y., Ouyang, X., Shao, Z., Wang, M., & Yu, J. (2025) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2025.3562422 · Cited by 23 · see citing works

Multi-Modal Validation and Domain Interaction Learning for Knowledge-Based Visual Question Answering

Xu, N., Gao, Y., Liu, A.-A., Tian, H., & Zhang, Y. (2024) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2024.3384270 · Cited by 21 · see citing works

Robust visual question answering via polarity enhancement and contrast

Peng, D., & Li, Z. (2024) · Neural Networks · doi:10.1016/j.neunet.2024.106560 · Cited by 20 · see citing works

Zero-shot Visual Question Answering with Language Model Feedback

Du, Y., Li, J., Tang, T., Zhao, W. X., & Wen, J.-R. (2023) · Findings of the Association for Computational Linguistics: ACL (Findings of ACL) · doi:10.18653/v1/2023.findings-acl.590 · Cited by 19 · see citing works

Towards a Search Engine for Machines: Unified Ranking for Multiple Retrieval-Augmented Large Language Models

Salemi, A., & Zamani, H. (2024) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3626772.3657733 · Cited by 22 · see citing works

MKGF: A multi-modal knowledge graph based RAG framework to enhance LVLMs for Medical visual question answering

Wu, Y., Lu, Y., Zhou, Y., Ding, Y., Liu, J., & Ruan, T. (2025) · Neurocomputing · doi:10.1016/j.neucom.2025.129999 · Cited by 18 · see citing works

A Simple Baseline for Knowledge-Based Visual Question Answering

Xenos, A., Stafylakis, T., Patras, I., & Tzimiropoulos, G. (2023) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2023.emnlp-main.919 · Cited by 21 · see citing works

DSAMR: Dual-Stream Attention Multi-hop Reasoning for knowledge-based visual question answering

Sun, Y., Zhu, Z., Zuo, Z., Li, K., Gong, S., & Qi, J. (2024) · Expert Systems with Applications · doi:10.1016/j.eswa.2023.123092 · Cited by 16 · see citing works

Situational Awareness Matters in 3D Vision Language Reasoning

Man, Y., Gui, L.-Y., & Wang, Y.-X. (2024) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52733.2024.01298 · Cited by 17 · see citing works

Filling the Image Information Gap for VQA: Prompting Large Language Models to Proactively Ask Questions

Wang, Z., Chen, C., Li, P., & Liu, Y. (2023) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2023.findings-emnlp.189 · Cited by 19 · see citing works

Coordinating explicit and implicit knowledge for knowledge-based VQA

Wang, Q., Liu, J., & Wu, W. (2024) · Pattern Recognition · doi:10.1016/j.patcog.2024.110368 · Cited by 15 · see citing works

UniBind: LLM-Augmented Unified and Balanced Representation Space to Bind Them All

Lyu, Y., Xu, Z., Zhou, J., & Wang, L. (2024) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52733.2024.02526 · Cited by 15 · see citing works

GPT-Based Knowledge Guiding Network for Commonsense Video Captioning

Yuan, M., Jia, G., & Bao, B. (2023) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2023.3330070 · Cited by 13 · see citing works

Cross-Modal Retrieval for Knowledge-Based Visual Question Answering

Lerner, P., Ferret, O., & Guinaudeau, C. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-56027-9_26 · Cited by 17 · see citing works

X-InstructBLIP: A Framework for Aligning Image, 3D, Audio, Video to LLMs and its Emergent Cross-Modal Reasoning

Panagopoulou, A., Xue, L., Yu, N., Li, J., Li, D., Joty, S., Xu, R., Savarese, S., Xiong, C., & Niebles, J. C. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-72995-9_11 · Cited by 37 · see citing works

Generate then Select: Open-ended Visual Question Answering Guided by World Knowledge

Fu, X., Zhang, S., Kwon, G., Perera, P., Zhu, H., Zhang, Y., Li, A. H., Wang, W. Y., Wang, Z., Castelli, V., et al. (2023) · Findings of the Association for Computational Linguistics: ACL (Findings of ACL) · doi:10.18653/v1/2023.findings-acl.147 · Cited by 12 · see citing works

Efficient Multimodal Selection for Retrieval in Knowledge-Based Visual Question Answering

Luo, L., Lai, H., Pan, Y., & Yin, J. P. (2025) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2025.3527032 · Cited by 12 · see citing works

DReX: Accurate and Scalable Dense Retrieval Acceleration via Algorithmic-Hardware Codesign

Quinn, D., Yücel, E. E., Prammer, M., Fan, Z., Kevin Skadron, Y., Patel, J. M., Martínez, J. F., & Alian, M. (2025) · Proceedings - International Symposium on Computer Architecture/Proceedings · doi:10.1145/3695053.3731079 · Cited by 11 · see citing works

Mix-tower: Light visual question answering framework based on exclusive self-attention mechanism

Chen, D., Chen, J., Yang, L., & Shang, F. (2024) · Neurocomputing · doi:10.1016/j.neucom.2024.127686 · Cited by 11 · see citing works

Entity-Focused Dense Passage Retrieval for Outside-Knowledge Visual Question Answering

Wu, J., & Mooney, R. J. (2022) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2022.emnlp-main.551 · Cited by 11 · see citing works

Object Attribute Matters in Visual Question Answering

Li, P., Si, Q., Fu, P., Lin, Z., & Wang, Y. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v38i17.29816 · Cited by 10 · see citing works

End-to-end Knowledge Retrieval with Multi-modal Queries

Luo, M., Fang, Z., Gokhale, T., Yang, Y., & Baral, C. R. (2023) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2023.acl-long.478 · Cited by 13 · see citing works

Combo of Thinking and Observing for Outside-Knowledge VQA

Si, Q., Mo, Y., Lin, Z., Ji, H., & Wang, W. (2023) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2023.acl-long.614 · Cited by 13 · see citing works

Unifying Text, Tables, and Images for Multimodal Question Answering

Luo, H., Shen, Y. J., & Deng, Y. (2023) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2023.findings-emnlp.626 · Cited by 10 · see citing works

Diff-ZsVQA: Zero-shot Visual Question Answering with Frozen Large Language Models Using Diffusion Model

Xu, Q., Li, J., Tian, Y., Zhou, L., Zhang, F., & Huang, R. (2025) · Expert Systems with Applications · doi:10.1016/j.eswa.2025.126951 · Cited by 9 · see citing works

Prompting Large Language Models with Fine-Grained Visual Relations from Scene Graph for Visual Question Answering

Liu, J., Fang, C., Li, L., Li, B., Hu, D., & Ma, C. (2024) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp48485.2024.10448321 · Cited by 9 · see citing works

Q&A Prompts: Discovering Rich Visual Clues through Mining Question-Answer Prompts for VQA requiring Diverse World Knowledge

Wang, H., & Ge, W. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-72946-1_16 · Cited by 8 · see citing works

Enhancing few-shot KB-VQA with panoramic image captions guided by Large Language Models

Qiang, P., Tan, H., Li, X., Wang, D., Li, R., Sun, X., Zhang, H., & Liang, J. (2025) · Neurocomputing · doi:10.1016/j.neucom.2025.129373 · Cited by 8 · see citing works

Language Models are Causal Knowledge Extractors for Zero-shot Video Question Answering

Su, H.-T., Niu, Y., Lin, X., Hsu, W. H., & Chang, S. (2023) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw59228.2023.00523 · Cited by 8 · see citing works

Improved Image Captioning Via Knowledge Graph-Augmented Models

Santiesteban, S. S., Atito, S., Awais, M., Song, Y.-Z., & Kittler, J. (2024) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp48485.2024.10447637 · Cited by 8 · see citing works

Multimodal Natural Language Explanation Generation for Visual Question Answering Based on Multiple Reference Data

Zhu, H., Togo, R., Ogawa, T., & Haseyama, M. (2023) · Electronics · doi:10.3390/electronics12102183 · Cited by 8 · see citing works

Historical visual question answering with large language model for Augmented Reality-assisted Human–Robot Collaboration

Lv, J., Si, J., Gao, D., & Bao, J. (2025) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2025.10.005 · Cited by 6 · see citing works

Learning to Supervise Knowledge Retrieval Over a Tree Structure for Visual Question Answering

Xu, N., Lu, Z., Tian, H., Kang, R., Cao, J., Zhang, Y., & Liu, A.-A. (2024) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2024.3355638 · Cited by 6 · see citing works

Caption matters: a new perspective for knowledge-based visual question answering

Feng, B., Ruan, S., Wu, L., Liu, H., Zhang, K., Zhang, K., Liu, Q., & Chen, E. (2024) · Knowledge and Information Systems · doi:10.1007/s10115-024-02166-8 · Cited by 6 · see citing works

RK-VQA: Rational knowledge-aware fusion-in-decoder for knowledge-based visual question answering

Chen, W., Huang, X. Q., Liu, Z., Liu, J., Yin, H., & Yo, L. (2025) · Information Fusion · doi:10.1016/j.inffus.2025.102969 · Cited by 5 · see citing works

Cross-Modal Representation Learning

Yao, Y., Liu, Z., Lin, Y., & Sun, M. (2023) · Springer eBooks · doi:10.1007/978-981-99-1600-9_7 · Cited by 5 · see citing works

KAFA: Rethinking Image Ad Understanding with Knowledge-Augmented Feature Adaptation of Vision-Language Models

Jia, Z., Narayana, P., Akula, A., Pruthi, G., Su, H., Basu, S., & Jampani, V. (2023) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2023.acl-industry.74 · Cited by 4 · see citing works

MM-Reasoner: A Multi-Modal Knowledge-Aware Framework for Knowledge-Based Visual Question Answering

Khademi, M., Yang, Z., Frujeri, F. V., & Zhu, C. (2023) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2023.findings-emnlp.437 · Cited by 4 · see citing works

Human-inspired Perspectives: A Survey on AI Long-term Memory

He, Z., Lin, W., Zheng, H., Zhang, F., Jones, M. W., Aitchison, L., Xu, X., Liu, M., Kristensson, P. O., & Shen, J. (2024) · arXiv · doi:10.48550/arxiv.2411.00489 · Cited by 3 · see citing works

Structural-temporal coupling anomaly detection with dynamic graph transformer

Zong, C., Zhuang, Y., Shao, J., & Lu, W. (2026) · Data Mining and Knowledge Discovery · doi:10.1007/s10618-025-01176-6 · Cited by 3 · see citing works

AI in Literature Reviews: a survey of current and emerging methods

Saied, M., Mokhtar, N., Badr, A., Adel, M., Boles, P., & Khoriba, G. A. (2024) · International Mobile, Intelligent, and Ubiquitous Computing Conference (MIUCC) · doi:10.1109/miucc62295.2024.10783597 · Cited by 3 · see citing works

AdQuestA: Knowledge-Guided Visual Question Answer Framework for Advertisements

Choudhary, N., Goyal, P., Siwatch, D., Chandak, A., Mahajan, H., Khurana, V., & Kumar, Y. (2025) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv61041.2025.00567 · Cited by 4 · see citing works

Outside Knowledge Visual Question Answering Version 2.0

Reichman, B., Sundar, A., Richardson, C., Zubatiy, T., Chowdhury, P., Shah, A., Truxal, J., Grimes, M., Shah, D., Chee, W. J., et al. (2023) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp49357.2023.10096074 · Cited by 3 · see citing works

Images in Language Space: Exploring the Suitability of Large Language Models for Vision & Language Tasks

Hakimov, S., & Schlangen, D. (2023) · Findings of the Association for Computational Linguistics: ACL (Findings of ACL) · doi:10.18653/v1/2023.findings-acl.894 · Cited by 3 · see citing works

Towards a Unified Model for Generating Answers and Explanations in Visual Question Answering

Whitehouse, C., Weyde, T., & Madhyastha, P. (2023) · Findings of the Association for Computational Linguistics: EACL · doi:10.18653/v1/2023.findings-eacl.126 · Cited by 3 · see citing works

Zero-Shot Knowledge-Based Visual Question Answering with Frozen Language Models

Liu, J., Zhang, L., Cao, C., Shi, Y., Mu, C., & Li, J. (2025) · Big Data Mining and Analytics · doi:10.26599/bdma.2025.9020032 · Cited by 2 · see citing works

Mitigating Inherent Bias of Answer Heuristic Based Frameworks in Knowledge-Based Visual Question Answering

Lu, J., Jiang, M., Kong, J., Zhuang, D., & Lu, M. (2025) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2025.3645641 · Cited by 2 · see citing works

Analysis of Transformer Model Applications

Cabrera-Bermejo, M. I., del Jesús, M. J., Rivera, A. J., Elizondo, D. A., Charte, F., & Pérez-Godoy, M. D. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-40725-3_20 · Cited by 2 · see citing works

Toward Multi-Granularity Decision-Making: Explicit Visual Reasoning with Hierarchical Knowledge

Zhang, Y., Chen, S., & Zhao, Q. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.00243 · Cited by 2 · see citing works

Multimodal Information Retrieval

Luo, M., Gokhale, T., Varshney, N., Yang, Y., & Baral, C. R. (2024) · Synthesis lectures on computer vision · doi:10.1007/978-3-031-57816-8_3 · Cited by 2 · see citing works

SCAG: Semantic Co-occurring Attention Guided Alignment for Knowledge-based Visual Question Answering

Liu, Z., Yang, K., Weng, Y., He, Z., Liu, X., & Gao, H. (2025) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/3734220 · Cited by 2 · see citing works

ICQ-TransE: LLM-Enhanced Image-Caption-Question Translating Embeddings for Knowledge-Based Visual Question Answering

Liu, H., Wang, B., Li, X., Sun, Y., Hu, Y., & Yin, B. (2025) · IEEE Transactions on Artificial Intelligence · doi:10.1109/tai.2025.3575553 · Cited by 2 · see citing works

On Advances in Text Generation from Images Beyond Captioning: A Case Study in Self-Rationalization

Palaskar, S., Bhagia, A., Bisk, Y., Metze, F., Black, A. W., & Marasović, A. (2022) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2022.findings-emnlp.194 · Cited by 3 · see citing works

Interpretable Visual Question Answering Referring to Outside Knowledge

Zhu, H., Togo, R., Ogawa, T., & Haseyama, M. (2023) · Proceedings - International Conference on Image Processing · doi:10.1109/icip49359.2023.10222423 · Cited by 3 · see citing works

Cross-Modal Dense Passage Retrieval for Outside Knowledge Visual Question Answering

Reichman, B., & Heck, L. P. (2023) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw60793.2023.00304 · Cited by 3 · see citing works

GRACE: Graph-Based Contextual Debiasing for Fair Visual Question Answering

Zhang, Y., Jiang, M. X., & Zhao, Q. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-72643-9_11 · Cited by 1 · see citing works

Toward profundity and precision: Reinventing knowledge retrieval capabilities guided by human cognition

Wang, C., Zhang, L., & Zhou, Y. (2025) · Knowledge-Based Systems · doi:10.1016/j.knosys.2025.113711 · Cited by 2 · see citing works

AFSPrompt: An Axiomatic Fuzzy Set Prompt Pipeline for Knowledge-Based VQA

Wang, Z., Lang, Q., Liu, X., & Zhang, H. (2025) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2025.3573267 · Cited by 1 · see citing works

Learning to Rank for Multiple Retrieval-Augmented Models through Iterative Utility Maximization

Salemi, A., & Zamani, H. (2025) · ACM SIGIR International Conference on Theory of Information Retrieval (ICTIR) · doi:10.1145/3731120.3744584 · Cited by 5 · see citing works

QC 2 -VQG: Question context complement for visual question generation

Zhang, Y., Liu, X., Lu, Z., Guo, W., Liu, X., & Yan, R. (2025) · Knowledge-Based Systems · doi:10.1016/j.knosys.2025.114306 · Cited by 1 · see citing works

Bootstrapping Large Language Models with Outsideknowledge for Knowledge-based Visual Question Answering

Min, Y., Sun, Y., Zhu, Y., Zhu, J., & Zhang, B. (2026) · Machine Intelligence Research · doi:10.1007/s11633-025-1591-z · Cited by 1 · see citing works

Effective Retrieval Augmentation for Knowledge-Based Vision Question Answering

Deng, J. (2024) · International Conference on Behavioral, Economic, and Socio-Cultural Computing · doi:10.1109/besc64747.2024.10780559 · Cited by 1 · see citing works

TAG: Triple Alignment With Rationale Generation for Knowledge-Based Visual Question Answering

Cai, S., Lin, X., Xu, W., Wu, J., Jin, T., Zhao, Z., Wu, F. Q., & Yu, J. (2025) · IEEE Transactions on Big Data · doi:10.1109/tbdata.2025.3600012 · Cited by 1 · see citing works

Dynamic Alternative Attention for Visual Question Answering

Liu, X., Guo, W., Zhang, Y., & Zhang, Y. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-20309-1_33

Conclusions and Research Trends

Gao, J., Xiong, C., Bennett, P. N., & Craswell, N. (2023) · The information retrieval series · doi:10.1007/978-3-031-23080-6_9

Mutant Texts: A Technique for Uncovering Unexpected Inconsistencies in Large-Scale Vision-Language Models

Liang, M., Liu, Z., & Larson, M. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-53302-0_16

Outside-Knowledge Visual Question Answering for Visual Impaired People

Sun, Y., Si, Q., Lin, Z., Wang, W., & Mei, T. (2023) · IEEE International Conference on Medical Artificial Intelligence (MedAI) · doi:10.1109/medai59581.2023.00014

A Comprehensive Review and Open Challenges on Visual Question Answering Models

Shaik, F. A., Koshti, D., Gupta, A., Kalla, M., & Sharma, A. (2023) · Aibi revista de investigación administración e ingeniería · doi:10.15649/2346030x.3370

Semi-Supervised Implicit Augmentation for Data-Scarce VQA

Dodla, B., Hegde, K., & Rajagopalan, A. N. (2024) · doi:10.3390/cmsf2024009003

A Reinforced Passage Interactive Retrieval Framework Incorporating Implicit Knowledge for KB-VQA

Zheng, H., Sun, T., Zhang, Z., Liu, H., Liu, G., Yang, Z., & Wang, X. (2024) · Lecture notes in computer science · doi:10.1007/978-981-97-5615-5_20

RAVL: A Retrieval-Augmented Visual Language Model Framework for Knowledge-Based Visual Question Answering

Chai, N., Zou, D., Liu, J., Wang, H., Yang, Y., & Song, X. (2024) · Lecture notes in computer science · doi:10.1007/978-981-97-9437-9_31

Imagination-Augmented Natural Language Understanding

Lu, Y., Zhu, W., Wang, X. E., Eckstein, M. P., & Wang, W. Y. (2022) · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · doi:10.18653/v1/2022.naacl-main.326 · Cited by 19 · see citing works

KAFA: Rethinking Image Ad Understanding with Knowledge-Augmented Feature Adaptation of Vision-Language Models

Jia, Z., Narayana, P., Akula, A., Pruthi, G., Su, H., Basu, S., & Jampani, V. (2023) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2023.acl-industry.74 · Cited by 4 · see citing works

ReAugKD: Retrieval-Augmented Knowledge Distillation For Pre-trained Language Models

Zhang, J., Muhamed, A., Anantharaman, A., Wang, G., Chen, C., Zhong, K., Cui, Q., Xu, Y., Zeng, B., Chilimbi, T. M., et al. (2023) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2023.acl-short.97 · Cited by 12 · see citing works

QAVA: Query-Agnostic Visual Attack to Large Vision-Language Models

Zhang, Y., Xie, R., Chen, J., Sun, X., Kang, Z., & Wang, Y. (2025) · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · doi:10.18653/v1/2025.naacl-long.512 · Cited by 1 · see citing works

Advancement in Graph Understanding: A Multimodal Benchmark and Fine-Tuning of Vision-Language Models

Ai, Q., Li, J., Dai, J., Zhou, J., Liu, L., Jiang, H., & Shi, S. (2024) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2024.acl-long.404 · Cited by 2 · see citing works