Akata, Zeynep

Generative Adversarial Text to Image Synthesis

Reed, S., Akata, Z., Yan, X., Logeswaran, L., Schiele, B., & Lee, H. (2016) · arXiv

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 2,494

Zero-Shot Learning—A Comprehensive Evaluation of the Good, the Bad and the Ugly

Xian, Y., Lampert, C. H., Schiele, B., & Akata, Z. (2019) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 1,678

Feature Generating Networks for Zero-Shot Learning

Xian, Y., Lorenz, T., Schiele, B., & Akata, Z. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition

Domain Adaptation and Few-Shot LearningGenerative Adversarial Networks and Image Synthesis

Cited by 1,080

Zero-Shot Learning — The Good, the Bad and the Ugly

Xian, Y., Schiele, B., & Akata, Z. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 891

Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders

Schönfeld, E., Ebrahimi, S., Sinha, S., Darrell, T., & Akata, Z. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 747

Generating Visual Explanations

Hendricks, L. A., Akata, Z., Rohrbach, M., Donahue, J., Schiele, B., & Darrell, T. (2016) · Lecture Notes in Computer Science

Multimodal Machine Learning ApplicationsExplainable Artificial Intelligence (XAI)

Cited by 534

Multimodal Explanations: Justifying Decisions and Pointing to the Evidence

Park, D. H., Hendricks, L. A., Akata, Z., Rohrbach, A., Schiele, B., Darrell, T., & Rohrbach, M. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition

Explainable Artificial Intelligence (XAI)Multimodal Machine Learning Applications

Cited by 418

A Research Agenda for Hybrid Intelligence: Augmenting Human Intellect With Collaborative, Adaptive, Responsible, and Explainable Artificial Intelligence

Akata, Z., Balliet, D., de Rijke, M., Dignum, F., Dignum, V., Eiben, G., Fokkens, A., Grossi, D., Hindriks, K., Hoos, H., et al. (2020) · Computer

Human-Automation Interaction and SafetyArtificial Intelligence Applications

Cited by 415

Explainable AI: The New 42?

Goebel, R., Chander, A., Holzinger, K., Lecue, F., Akata, Z., Stumpf, S., Kieseberg, P., & Holzinger, A. (2018) · Lecture Notes in Computer Science

Explainable Artificial Intelligence (XAI)Logic, Reasoning, and Knowledge

Cited by 259

Grounding visual explanations

Hendricks, L. A., Hu, R., Darrell, T., & Akata, Z. (2018) · Lecture notes in computer science

Explainable Artificial Intelligence (XAI)Multimodal Machine Learning Applications

Cited by 171

How should the advancement of large language models affect the practice of science?

Binz, M., Alaniz, S., Roskies, A., Aczel, B., Bergstrom, C. T., Allen, C., Schad, D., Wulff, D., West, J. D., Zhang, Q., et al. (2025) · Proceedings of the National Academy of Sciences

Artificial Intelligence ApplicationsEthics and Social Impacts of AI

Cited by 74

e-ViL: A Dataset and Benchmark for Natural Language Explanations in Vision-Language Tasks

Kayser, M., Camburu, O.-M., Salewski, L., Emde, C., Do, V., Akata, Z., & Lukasiewicz, T. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Multimodal Machine Learning ApplicationsExplainable Artificial Intelligence (XAI)

Cited by 68

Generating Visual Explanations

Hendricks, L. A., Akata, Z., Rohrbach, M., Donahue, J., Schiele, B., & Darrell, T. (2016) · arXiv

Multimodal Machine Learning ApplicationsExplainable Artificial Intelligence (XAI)

Cited by 64

CLEVR-X: A Visual Reasoning Dataset for Natural Language Explanations

Salewski, L., Koepke, A. S., Lensch, H. P. A., & Akata, Z. (2022) · Lecture Notes in Computer Science

Multimodal Machine Learning ApplicationsExplainable Artificial Intelligence (XAI)

Cited by 20

Meta-in-context learning in large language models

Coda-Forno, J., Binz, M., Akata, Z., Botvinick, M., Wang, J., & Schulz, E. (2023) · Advances in Neural Information Processing Systems 36

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 20

Towards Recognizing Unseen Categories in Unseen Domains

Mancini, M., Akata, Z., Ricci, E., & Caputo, B. (2020) · Lecture Notes in Computer Science

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 9

Mantis: Lightweight Foundation Model for Time Series Classification

Feofanov, V., Wen, S., Xie, S., Roschmann, S., Alonso, M., Guo, H., Ilbert, R., Tiomoko, M., Bouniot, Q., Akata, Z., et al. (2025) · arXiv

Time Series Analysis and ForecastingMusic and Audio Processing

Cited by 1

WikiBigEdit: Understanding the Limits of Lifelong Knowledge Editing in LLMs

Thede, L., Roth, K., Bethge, M., Akata, Z., & Hartvigsen, T. (2025) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 0