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Deep Residual Learning for Image Recognition

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A Style-Based Generator Architecture for Generative Adversarial Networks

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Perceptual Losses for Real-Time Style Transfer and Super-Resolution

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GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium

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Improved Techniques for Training GANs

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Analyzing and Improving the Image Quality of StyleGAN

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Representation Learning with Contrastive Predictive Coding

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Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation

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Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations

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Arbitrary Style Transfer in Real-Time with Adaptive Instance Normalization

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High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs

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Generative Adversarial Networks

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Instance Normalization: The Missing Ingredient for Fast StylizationPreprint

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Billion-scale similarity search with GPUs

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GQA: A New Dataset for Real-World Visual Reasoning and Compositional Question Answering

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Gaussian Error Linear Units (GELUs)

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Spectral Normalization for Generative Adversarial Networks

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HuggingFace's Transformers: State-of-the-art Natural Language Processing

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Pixel Recurrent Neural NetworksPreprint

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StackGAN: Text to Photo-Realistic Image Synthesis with Stacked Generative Adversarial Networks

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Semantic Image Synthesis With Spatially-Adaptive Normalization

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Conditional Image Synthesis With Auxiliary Classifier GANsPreprint

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Unsupervised Learning of Visual Representations by Solving Jigsaw Puzzles

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Neural Discrete Representation Learning

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Generative Adversarial Text to Image Synthesis

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LXMERT: Learning Cross-Modality Encoder Representations from Transformers

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

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AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks

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Unified Language Model Pre-training for Natural Language Understanding and Generation

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StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks

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VideoBERT: A Joint Model for Video and Language Representation Learning

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Data-Efficient Image Recognition with Contrastive Predictive Coding

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

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Unified Vision-Language Pre-Training for Image Captioning and VQA

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

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Visual7W: Grounded Question Answering in Images

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Generating diverse high-fidelity images with vq-vae-2

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DM-GAN: Dynamic Memory Generative Adversarial Networks for Text-To-Image Synthesis

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Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space

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Geometric GANPreprint

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A Corpus for Reasoning about Natural Language Grounded in Photographs

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Making the V in VQA Matter: Elevating the Role of Image Understanding in Visual Question Answering

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cGANs with Projection DiscriminatorPreprint

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Mask-Predict: Parallel Decoding of Conditional Masked Language Models

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Generative Adversarial Networks

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12-in-1: Multi-Task Vision and Language Representation Learning

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In Defense of Grid Features for Visual Question Answering

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Inferring Semantic Layout for Hierarchical Text-to-Image Synthesis

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Pixel-BERT: Aligning Image Pixels with Text by Deep Multi-Modal TransformersPreprint

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cGANs with Projection Discriminator

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UNITER: Learning UNiversal Image-TExt Representations

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UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-TrainingPreprint

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Controllable Text-to-Image GenerationPreprint

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ImageBERT: Cross-modal Pre-training with Large-scale Weak-supervised Image-Text DataPreprint

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Revising the evolutionary computation abstraction

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Fusion of Detected Objects in Text for Visual Question Answering

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BERT has a Mouth, and It Must Speak: BERT as a Markov Random Field Language ModelPreprint

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COCO-GAN: Generation by Parts via Conditional Coordinating

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Hierarchical Implicit Models and Likelihood-Free Variational InferencePreprint

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Learning Representations by Predicting Bags of Visual Words

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Text2Scene: Generating Compositional Scenes From Textual Descriptions

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Selfie: Self-supervised Pretraining for Image EmbeddingPreprint

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A Generalized Framework of Sequence Generation with Application to Undirected Sequence ModelsPreprint

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M-BERT: Injecting Multimodal Information in the BERT StructurePreprint

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Probabilistically Masked Language Model Capable of Autoregressive Generation in Arbitrary Word Order

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Probing Text Models for Common Ground with Visual RepresentationsPreprint

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BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

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Multimodal learning with transformers: A survey

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Demystifying the Draft EU Artificial Intelligence Act — Analysing the good, the bad, and the unclear elements of the proposed approach

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LayoutLMv3: Pre-training for Document AI with Unified Text and Image Masking

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Unifying Vision-and-Language Tasks via Text GenerationPreprint

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Incremental Transformer Structure Enhanced Image Inpainting with Masking Positional Encoding

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Multi-Modal Understanding and Generation for Medical Images and Text via Vision-Language Pre-Training

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A Survey of Vision-Language Pre-Trained Models

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DALL-EVAL: Probing the Reasoning Skills and Social Biases of Text-to-Image Generation Models

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Multimodal Image Synthesis and Editing: The Generative AI Era

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TIFA: Accurate and Interpretable Text-to-Image Faithfulness Evaluation with Question Answering

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Multimodal Pretraining Unmasked: A Meta-Analysis and a Unified Framework of Vision-and-Language BERTs

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Survey of Different Large Language Model Architectures: Trends, Benchmarks, and Challenges

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Demystifying the Draft EU Artificial Intelligence Act

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WenLan: Bridging Vision and Language by Large-Scale Multi-Modal Pre-TrainingPreprint

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LRCN: Layer-residual Co-Attention Networks for visual question answering

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A Prompt Log Analysis of Text-to-Image Generation Systems

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Mind ascribed to AI and the appreciation of AI-generated art

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Heterogeneous Attention Network for Effective and Efficient Cross-modal Retrieval

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Scaling-up medical vision-and-language representation learning with federated learning

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Integrating Visuospatial, Linguistic, and Commonsense Structure into Story Visualization

Maharana, A., & Bansal, M. (2021) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2021.emnlp-main.543 · Cited by 40 · see citing works

Unifying Multimodal Transformer for Bi-directional Image and Text Generation

Huang, Y., Xue, H., Liu, B., & Lu, Y. (2021) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3474085.3481540 · Cited by 37 · see citing works

Show Me What and Tell Me How: Video Synthesis via Multimodal Conditioning

Han, L., Ren, J., Lee, H.-Y., Barbieri, F., Olszewski, K., Minaee, S., Metaxas, D., & Tulyakov, S. (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/cvpr52688.2022.00360 · Cited by 38 · see citing works

OpenViVQA: Task, dataset, and multimodal fusion models for visual question answering in Vietnamese

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Towards General Purpose Vision Systems: An End-to-End Task-Agnostic Vision-Language Architecture

Gupta, T., Kamath, A., Kembhavi, A., & Hoiem, D. (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/cvpr52688.2022.01591 · Cited by 54 · see citing works

See and Learn More: Dense Caption-Aware Representation for Visual Question Answering

Bi, Y., Jiang, H., Hu, Y., Sun, Y., & Yin, B. (2023) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2023.3291379 · Cited by 34 · see citing works

Txt2Vid: Ultra-Low Bitrate Compression of Talking-Head Videos via Text

Tandon, P., Chandak, S., Pataranutaporn, P., Liu, Y., Mapuranga, A. M., Maes, P., Weissman, T., & Sra, M. (2022) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2022.3221953 · Cited by 32 · see citing works

Multimodal Dialogue Response Generation

Sun, Q., Wang, Y., Xu, C., Zheng, K., Yang, Y., Hu, H., Xu, F., Zhang, J., Geng, X., & Jiang, D. (2022) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2022.acl-long.204 · Cited by 31 · see citing works

A survey on knowledge-enhanced multimodal learning

Lymperaiou, M., & Stamou, G. B. (2024) · Artificial Intelligence Review · doi:10.1007/s10462-024-10825-z · Cited by 35 · see citing works

Toward the unification of generative and discriminative visual foundation model: a survey

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UFC-BERT: Unifying Multi-Modal Controls for Conditional Image SynthesisPreprint

Zhang, Z., Ma, J., Zhou, C., Men, R., Li, Z., Ding, M., Tang, J., Zhou, J., & Yang, H. (2021) · arXiv (Cornell University) · Cited by 26 · see citing works

Rethinking and Improving Feature Pyramids for One-Stage Referring Expression Comprehension

Suo, W., Sun, M., Wang, P., Zhang, Y., & Wu, Q. (2022) · IEEE Transactions on Image Processing · doi:10.1109/tip.2022.3227466 · Cited by 23 · see citing works

A Multimodal Large Language Model Framework for Intelligent Perception and Decision-Making in Smart Manufacturing

Wang, T., Zhang, B., Jiang, D., & Li, D. (2025) · Sensors · doi:10.3390/s25103072 · Cited by 27 · see citing works

Inspecting the Geographical Representativeness of Images from Text-to-Image Models

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Transitioning from TinyML to Edge GenAI: A Review

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MobiVQA

Cao, Q., Khanna, P., Lane, N. D., & Balasubramanian, A. (2022) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3534619 · Cited by 17 · see citing works

Multi-task framework based on feature separation and reconstruction for cross-modal retrieval

Zhang, L., & Wu, X. (2021) · Pattern Recognition · doi:10.1016/j.patcog.2021.108217 · Cited by 16 · see citing works

Towards General Purpose Vision SystemsPreprint

Gupta, T., Kamath, A., Kembhavi, A., & Hoiem, D. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2104.00743 · Cited by 16 · see citing works

IRGen: Generative Modeling for Image Retrieval

Zhang, Y., Zhang, T., Chen, D., Wang, Y., Chen, Q., Xie, X., Sun, H., Deng, W., Zhang, Q., Yang, F., et al. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-72633-0_2 · Cited by 15 · see citing works

Learning to Agree on Vision Attention for Visual Commonsense Reasoning

Li, Z., Guo, Y., Wang, K., Liu, F., Nie, L., & Kankanhalli, M. (2023) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2023.3275874 · Cited by 15 · see citing works

Climate futures: Machine learning from cli-fi

Sánchez-Querubín, N., & Niederer, S. (2022) · Convergence The International Journal of Research into New Media Technologies · doi:10.1177/13548565221135715 · Cited by 13 · see citing works

A Critical Analysis of Benchmarks, Techniques, and Models in Medical Visual Question Answering

Al-Hadhrami, S. A., Menaï, M. E. B., Al-Ahmadi, S. A., & Alnafessah, A. (2023) · IEEE Access · doi:10.1109/access.2023.3335216 · Cited by 13 · see citing works

Diffusion-driven Incomplete Multimodal Learning for Air Quality Prediction

Fan, J., Qi, M., Liu, L., & Ma, H. (2024) · ACM Transactions on Internet of Things · doi:10.1145/3702243 · Cited by 10 · see citing works

Invariant Meets Specific: A Scalable Harmful Memes Detection Framework

Yang, C., Zhu, F., Han, J., & Hu, S. (2023) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3581783.3611761 · Cited by 10 · see citing works

Advancing Vietnamese Visual Question Answering with Transformer and Convolutional Integration

Nguyen, N. S., Nguyen, V. S., & Le, T. (2024) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2024.109474 · Cited by 8 · see citing works

Diagnostic Benchmark and Iterative Inpainting for Layout-Guided Image Generation

Cho, J., Li, L., Yang, Z., Gan, Z., Wang, L., & Bansal, M. (2024) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw63382.2024.00537 · Cited by 8 · see citing works

DiMBERT: Learning Vision-Language Grounded Representations with Disentangled Multimodal-Attention

Liu, F., Wu, X., Ge, S., Ren, X., Fan, W., Sun, X., & Zou, Y. (2021) · ACM Transactions on Knowledge Discovery from Data · doi:10.1145/3447685 · Cited by 8 · see citing works

U-BERT for Fast and Scalable Text-Image Retrieval

Yu, T., Fei, H., & Li, P. (2022) · ACM SIGIR International Conference on Theory of Information Retrieval (ICTIR) · doi:10.1145/3539813.3545148 · Cited by 6 · see citing works

How to Practice VQA on a Resource-limited Target Domain

Zhang, M., Hwa, R., & Kovashka, A. (2023) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv56688.2023.00443 · Cited by 6 · see citing works

Iconary: A Pictionary-Based Game for Testing Multimodal Communication with Drawings and Text

Clark, C., Salvador, J., Schwenk, D., Bonafilia, D., Yatskar, M., Kolve, E., Herrasti, A., Choi, J., Mehta, S., Skjonsberg, S., et al. (2021) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2021.emnlp-main.141 · Cited by 6 · see citing works

Pretraining Multi-modal Representations for Chinese NER Task with Cross-Modality Attention

Mai, C., Qiu, M., Luo, K., Peng, Z., Liu, J., Yuan, C., & Huang, Y. (2022) · ACM International Conference on Web Search and Data Mining (WSDM) · doi:10.1145/3488560.3498450 · Cited by 6 · see citing works

Inferring spatial relations from textual descriptions of images

Etxano, A. E., Azkune, G., de Lacalle, O. L., Arganda‐Carreras, I., Soroa, A., & Agirre, E. (2021) · Pattern Recognition · doi:10.1016/j.patcog.2021.107847 · Cited by 5 · see citing works

InterREC: An Interpretable Method for Referring Expression Comprehension

Wang, W., Pagnucco, M., Xu, C., & Song, Y. (2023) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2023.3251111 · Cited by 5 · see citing works

MISSRAG: Addressing the Missing Modality Challenge in Multimodal Large Language Models

Pipoli, V., Saporita, A., Bolelli, F., Cornia, M., Baraldi, L., Grana, C., Cucchiara, R., & Ficarra, E. (2025) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51701.2025.00308 · Cited by 4 · see citing works

Describing the APIs comprehensively: Obtaining the holistic representations from multiple modalities data for different tasks

Li, X., Liu, L., Chen, Z., Liu, Y., & Liu, H. (2023) · Information and Software Technology · doi:10.1016/j.infsof.2023.107188 · Cited by 4 · see citing works

Foundation Models for Speech, Images, Videos, and Control

Paaß, G., & Giesselbach, S. (2023) · Artificial intelligence: foundations, theory, and algorithms/Artificial intelligence: Foundations, theory, and algorithms · doi:10.1007/978-3-031-23190-2_7 · Cited by 5 · see citing works

Conversational Composed Retrieval with Iterative Sequence Refinement

Hao, W., Wang, S., Xue, Z., Chen, S., & Huang, Q. (2023) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3581783.3611885 · Cited by 4 · see citing works

No Head Left Behind – Multi-Head Alignment Distillation for Transformers

Zhao, T., Singh, K. Y., Appalaraju, S., Tang, P., Mahadevan, V., Manmatha, R., & Wu, Y. N. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v38i7.28583 · Cited by 4 · see citing works

Texture BERT for Cross-modal Texture Image Retrieval

Xu, Z., Yu, T., & Li, P. (2022) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/3511808.3557710 · Cited by 4 · see citing works

TIAR: Text-Image-Audio Retrieval with weighted multimodal re-ranking

Chi, P., Feng, Y., Zhou, M., Xiong, X., Wang, Y., & Qiang, B. (2023) · Applied Intelligence · doi:10.1007/s10489-023-04669-3 · Cited by 4 · see citing works

MixBERT for Image-Ad Relevance Scoring in Advertising

Yu, T., Li, X., Xie, J., Yin, R., Xu, Q. Y., & Li, P. (2021) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/3459637.3482143 · Cited by 4 · see citing works

EL-Attention: Memory Efficient Lossless Attention for GenerationPreprint

Yan, Y., Chen, J., Qi, W., Bhendawade, N., Gong, Y., Duan, N., & Zhang, R. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2105.04779 · Cited by 4 · see citing works

CIGLI: Conditional Image Generation from Language & Image

Lu, X., Ng, L. H. X., Fernandez, J., & Zhu, H. (2021) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw54120.2021.00349 · Cited by 3 · see citing works

Knowledge-Embedded Mutual Guidance for Visual Reasoning

Zheng, W., Yan, L., Chen, L., Li, Q., & Wang, F. (2023) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2023.3310892 · Cited by 3 · see citing works

PAT: Parallel Attention Transformer for Visual Question Answering in Vietnamese

Nguyen, N. H., & Nguyen, K. V. (2023) · International Conference on Multimedia Analysis and Pattern Recognition (MAPR) · doi:10.1109/mapr59823.2023.10288833 · Cited by 4 · see citing works

Mismatch Quest: Visual and Textual Feedback for Image-Text Misalignment

Gordon, B., Bitton, Y., Shafir, Y., Garg, R., Chen, X., Lischinski, D., Cohen‐Or, D., & Szpektor, I. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-72998-0_18 · Cited by 3 · see citing works

Die Enkel von Locard

Povalej, R., Rittelmeier, H., Fähndrich, J., Berner, S., Honekamp, W., & Labudde, D. (2021) · Informatik-Spektrum · doi:10.1007/s00287-021-01393-5 · Cited by 3 · see citing works

Multi-VQG: Generating Engaging Questions for Multiple Images

Yeh, M.-H., Chen, V., Huang, T.-H., & Ku, L. (2022) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2022.emnlp-main.19 · Cited by 4 · see citing works

Emerging Trends of Multimodal Research in Vision and Language.Preprint

Uppal, S., Bhagat, S., Hazarika, D., Majumder, N., Poria, S., Zimmermann, R., & Zadeh, A. (2020) · arXiv (Cornell University) · Cited by 3 · see citing works

GDP: Generic Document Pretraining to Improve Document Understanding

Trivedi, A., Upadhyay, A., Mukhopadhyay, R., & Chaudhury, S. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-70533-5_13 · Cited by 2 · see citing works

Continual Learning: Forget-Free Winning Subnetworks for Video Representations

Kang, H., Yoon, J., Hwang, S. J., & Yoo, C. D. (2024) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2024.3518588 · Cited by 2 · see citing works

EM-LAST: Effective Multidimensional Latent Space Transport for an Unpaired Image-to-Image Translation With an Energy-Based Model

Han, G., Min, J., & Han, S. W. (2022) · IEEE Access · doi:10.1109/access.2022.3189352 · Cited by 2 · see citing works

A Picture is Worth a Thousand Words

Huang, Y., Liu, B., Fu, J., & Lu, Y. (2021) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3474085.3478561 · Cited by 1 · see citing works

Using Language-Based and Generative Deep Learning Models for Encoding Design Intentions and Modifying Architectural Design

Yousif, S. (2022) · Association of Collegiate Schools of Architecture Annual Meeting (ACSA) · doi:10.35483/acsa.am.110.32 · Cited by 1 · see citing works

Multimodal Large Language Models (MLLMs) for Object Detection from Thermal Images: Initial Experiments

Ashqar, H. I., Alhadidi, T. I., Elhenawy, M. M. Z., & Khanfar, N. O. (2025) · International Conference on Smart Applications, Communications and Networking (SmartNets) · doi:10.1109/smartnets65254.2025.11106847 · Cited by 1 · see citing works

Linguistic-Guided Feature Refinement For One-Stage Visual Grounding

Zhang, Z., & Xie, S. (2024) · International Conference on Computer Engineering and Application (ICCEA) · doi:10.1109/iccea62105.2024.10603864 · Cited by 1 · see citing works

Text-Image Generation Using Visual-Language Transformer Parallel Decoding

Fang, P., & Wang, F. (2024) · International Conference on Intelligent Computing and Signal Processing (ICSP) · doi:10.1109/icsp62122.2024.10743787 · Cited by 1 · see citing works

Enhancing Multimodal Information Extraction from Visually Rich Documents with 2D Positional Embeddings

Arshad, A., Moetesum, M., Hasan, A. U., & Faisal Shafait, B. (2024) · International Conference on Digital Image Computing: Techniques and Applications (DICTA) · doi:10.1109/dicta63115.2024.00087 · Cited by 1 · see citing works

HistoryCLIP: Adaptive Multi-modal Retrieval of Imbalanced Long-Tailed Archival Data

Alijani, F., Late, E., & Kumpulainen, S. (2025) · Lecture notes in computer science · doi:10.1007/978-3-032-05409-8_15 · Cited by 1 · see citing works

Rethinking the constraints of multimodal fusion: case study in Weakly-Supervised Audio-Visual Video ParsingPreprint

Wu, J., Jiang, Z., Wen, S., Men, A., & Wang, H. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2105.14430 · Cited by 1 · see citing works

Vision-and-Language Pretraining: Methods, Applications, and Future ChallengesPreprint

Nguyen, T., Nguyen, C.-D. T., Wu, X., Ng, S.-K., & Luu, A.-T. (2023) · Research Square · doi:10.21203/rs.3.rs-3120051/v1 · Cited by 1 · see citing works

Document Understanding with Deep Learning Techniques

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Multi-Tailed, Multi-Headed, Spatial Dynamic Memory refined Text-to-Image SynthesisPreprint

Seshadri, A. D., & Ravindran, B. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2110.08143

Iconary: A Pictionary-Based Game for Testing Multimodal Communication with Drawings and TextPreprint

Clark, C., Salvador, J., Schwenk, D., Bonafilia, D., Yatskar, M., Kolve, E., Herrasti, A., Choi, J., Mehta, S., Skjonsberg, S., et al. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2112.00800

JGRCAN: A Visual Question Answering Co-Attention Network via Joint Grid-Region Features

Liang, J., Xu, T., Chen, S., & Ao, Z. (2022) · Mathematical Problems in Engineering · doi:10.1155/2022/4554074

Text to fashion image synthesis Via CW-ControlGAN

Moradian, F., Azmi, R., Darvishi, H., & Khademhossein, M. (2024) · CSI International Symposium on Artificial Intelligence and Signal Processing · doi:10.1109/aisp61396.2024.10475289

Superpixel Semantics Representation and Pre-Training for Visionlanguage TasksPreprint

Zhang, S., Chen, Y., Sun, Y., Wang, F., Yang, J., Bai, L., & Gao, S. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4862102

Superpixel semantics representation and pre-training for vision–language tasks

Zhang, S., Chen, Y., Sun, Y., Wang, F., Yang, J., Bai, L., & Gao, S. (2024) · Neurocomputing · doi:10.1016/j.neucom.2024.128895

Can Linear Algebra Create Perfect Knockoffs?

Hemmens, C., & Robert, S. (2024) · Lecture notes in networks and systems · doi:10.1007/978-3-031-74491-4_81

Self-Attention-Based Text Encoder for Enhancing DMGAN Text-to-Image Generation

Gopalakrishnan, R., Naveen, S., Kalathil, S., & Sudeep, P. V. (2025) · IEEE Access · doi:10.1109/access.2025.3588762

Enhanced Image Captioning Model Using Winograd Convolution and Multi-objective Bayesian Optimization

Xu, M., Dong, Y., & Pan, K. (2025) · Communications in computer and information science · doi:10.1007/978-981-96-7178-6_20

Photo-realistic image generation using text descriptions in Indian languages: an exploration study

Gopalakrishnan, R., & Sudeep, P. V. (2025) · Sadhana · doi:10.1007/s12046-025-02946-0

ViPhoVQA: Toward a Phonemic-Based Method for Mitigating Rare and Out-of-Vocab Words in Vietnamese Text-Based Visual Question Answering

Nguyen, N. H., Nguyen, D.-V., To, H. Q., Đinh, Đ., Quan, T., & Nguyen, N. L.-T. (2025) · Lecture notes in computer science · doi:10.1007/978-3-032-09318-9_16

AI-Driven Image Generation: Algorithms, Architectures, Quality Assessment, and Applications—A Structured Narrative Review

Leszczuk, M., Zhang, Y., Farias, M. C. Q., Chandler, D. M., & Kalola, R. (2026) · Electronics · doi:10.3390/electronics15132891

Zero-shot text-to-image generation

Ramesh, A., Pavlov, M., Goh, G., Gray, S., Voss, C., Radford, A., Chen, M., & Sutskever, I. (2021) · arXiv · doi:10.48550/arxiv.2102.12092 · Cited by 2,417 · see citing works

ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision

Kim, W., Son, B., & Kim, I. (2021) · arXiv · doi:10.48550/arxiv.2102.03334 · Cited by 951 · see citing works

Language Models Can See: Plugging Visual Controls in Text GenerationPreprint

Su, Y., Lan, T., Liu, Y., Liu, F., Yogatama, D., Wang, Y., Kong, L., & Collier, N. (2022) · arXiv (Cornell University) · doi:10.48550/arxiv.2205.02655 · Cited by 42 · see citing works

Generating Images with Multimodal Language Models

Koh, J. Y., Fried, D., & Salakhutdinov, R. R. (2023) · neural information processing systems · doi:10.52202/075280-0939 · Cited by 85 · see citing works

Lumina-mGPT: Illuminate Flexible Photorealistic Text-to-Image Generation with Multimodal Generative PretrainingPreprint

Liu, D., Zhao, S., Zhuo, L., Lin, W., Xin, Y., Li, H., Qin, Q., Qiao, Y., Li, H., & Gao, P. (2024) · arXiv (Cornell University) · doi:10.48550/arxiv.2408.02657 · 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

LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Shi, W., Han, X., Zhou, C., Liang, W., Lin, X., Zettlemoyer, L., & YU, L. (2025) · neural information processing systems · doi:10.52202/085713-0310 · Cited by 6 · see citing works