Lisa Anne M Hendricks
Lisa Anne M Hendricks
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Cited by
Long-term recurrent convolutional networks for visual recognition and description
J Donahue, LA Hendricks, S Guadarrama, M Rohrbach, S Venugopalan, ...
Proceedings of the IEEE conference on computer vision and pattern …, 2015
Training compute-optimal large language models
J Hoffmann, S Borgeaud, A Mensch, E Buchatskaya, T Cai, E Rutherford, ...
arXiv preprint arXiv:2203.15556, 2022
Gemini: a family of highly capable multimodal models
G Team, R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, ...
arXiv preprint arXiv:2312.11805, 2023
Localizing moments in video with natural language
LA Hendricks, O Wang, E Shechtman, J Sivic, T Darrell, B Russell
Proceedings of the IEEE international conference on computer vision, 5803-5812, 2017
Scaling language models: Methods, analysis & insights from training gopher
JW Rae, S Borgeaud, T Cai, K Millican, J Hoffmann, F Song, J Aslanides, ...
arXiv preprint arXiv:2112.11446, 2021
Generating Visual Explanations
LA Hendricks, Z Akata, M Rohrbach, J Donahue, B Schiele, T Darrell
The 14th European Conference on Computer Vision (ECCV 2016), 2016
Ethical and social risks of harm from language models
L Weidinger, J Mellor, M Rauh, C Griffin, J Uesato, PS Huang, M Cheng, ...
arXiv preprint arXiv:2112.04359, 2021
Multimodal explanations: Justifying decisions and pointing to the evidence
DH Park, LA Hendricks, Z Akata, A Rohrbach, B Schiele, T Darrell, ...
Proceedings of the IEEE conference on computer vision and pattern …, 2018
Women also Snowboard: Overcoming Bias in Captioning Models
LA Hendricks, K Burns, K Saenko, T Darrell, A Rohrbach
Proceedings of the European Conference on Computer Vision (ECCV), 771-787, 2018
Taxonomy of risks posed by language models
L Weidinger, J Uesato, M Rauh, C Griffin, PS Huang, J Mellor, A Glaese, ...
Proceedings of the 2022 ACM Conference on Fairness, Accountability, and …, 2022
Object hallucination in image captioning
A Rohrbach, LA Hendricks, K Burns, T Darrell, K Saenko
arXiv preprint arXiv:1809.02156, 2018
Improving alignment of dialogue agents via targeted human judgements
A Glaese, N McAleese, M Trębacz, J Aslanides, V Firoiu, T Ewalds, ...
arXiv preprint arXiv:2209.14375, 2022
Deep Compositional Captioning: Describing Novel Object Categories without Paired Training Data
LA Hendricks, S Venugopalan, M Rohrbach, R Mooney, K Saenko, ...
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016
Deep learning for tactile understanding from visual and haptic data
Y Gao, LA Hendricks, KJ Kuchenbecker, T Darrell
2016 IEEE international conference on robotics and automation (ICRA), 536-543, 2016
Speaking the same language: Matching machine to human captions by adversarial training
R Shetty, M Rohrbach, LA Hendricks, M Fritz, B Schiele
Proceedings of the IEEE International Conference on Computer Vision, 4135-4144, 2017
Grounding visual explanations
LA Hendricks, R Hu, T Darrell, Z Akata
Proceedings of the European conference on computer vision (ECCV), 264-279, 2018
Captioning images with diverse objects
S Venugopalan, LA Hendricks, M Rohrbach, R Mooney, T Darrell, ...
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
M Reid, N Savinov, D Teplyashin, D Lepikhin, T Lillicrap, J Alayrac, ...
arXiv preprint arXiv:2403.05530, 2024
Challenges in detoxifying language models
J Welbl, A Glaese, J Uesato, S Dathathri, J Mellor, LA Hendricks, ...
arXiv preprint arXiv:2109.07445, 2021
Improving lstm-based video description with linguistic knowledge mined from text
S Venugopalan, LA Hendricks, R Mooney, K Saenko
arXiv preprint arXiv:1604.01729, 2016
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