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Clearly explaining a rationale for a classification decision to an end-user can be as important as the decision itself.
A model of inexact reasoning in medicine
Shortliffe, E.H., Buchanan, B.G.: · 1975
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An analysis of physician attitudes regarding computer-based clinical consultation systems
Teach, R.L., Shortliffe, E.H.: · 1981
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Introduction to wordnet: An on-line lexical database*
Miller, G.A., Beckwith, R., Fellbaum, C., Gross, D., Miller, K.J.: · 1990
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Simple statistical gradient-following algorithms for connectionist reinforcement learning
Williams, R.J.: · 1992
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Agents that learn to explain themselves
Johnson, W.L.: · 1994
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Long short-term memory
Hochreiter, S., Schmidhuber, J.: · 1997
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A review of explanation methods for bayesian networks
Lacave, C., Díez, F.J.: · 2002
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Bleu: a method for automatic evaluation of machine translation
Papineni, K., Roukos, S., Ward, T., Zhu, W.J.: · 2002
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An explainable artificial intelligence system for small-unit tactical behavior
Van Lent, M., Fisher, W., Mancuso, M.: · 2004
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Explainable artificial intelligence for training and tutoring
Lane, H.C., Core, M.G., Van Lent, M., Solomon, S., Gomboc, D.: · 2005
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Meteor: An automatic metric for mt evaluation with improved correlation with human judgments
Banerjee, S., Lavie, A.: · 2005
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Building explainable artificial intelligence systems
Core, M.G., Lane, H.C., Van Lent, M., Gomboc, D., Solomon, S., Rosenberg, M.: · 2006
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Imagenet: A large-scale hierarchical image database
Deng, J., Dong, W., Socher, R., Li, L.J., Li, K., Fei-Fei, L.: · 2009
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Baby talk: understanding and generating simple image descriptions
Kulkarni, G., Premraj, V., Dhar, S., Li, S., choi, Y., Berg, A., Berg, T.: · 2011
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The Caltech-UCSD Birds-200-2011 Dataset
Wah, C., Branson, S., Welinder, P., Perona, P., Belongie, S.: · 2011
Cited alongside, same era.
Imagenet classification with deep convolutional neural networks
Krizhevsky, A., Sutskever, I., Hinton, G.E.: · 2012
Cited alongside, same era.
Explaining robot actions
Lomas, M., Chevalier, R., Cross II, E.V., Garrett, R.C., Hoare, J., Kopack, M.: · 2012
Cited alongside, same era.
What makes paris look like paris?
Doersch, C., Singh, S., Gupta, A., Sivic, J., Efros, A.: · 2012
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Decaf: A deep convolutional activation feature for generic visual recognition
Donahue, J., Jia, Y., Vinyals, O., Hoffman, J., Zhang, N., Tzeng, E., Darrell, T.: · 2013
Cited alongside, same era.
How do you tell a blackbird from a crow?
Berg, T., Belhumeur, P.: · 2013
Cited alongside, same era.
Deep visual-semantic alignments for generating image descriptions
Karpathy, A., Li, F.: · 2015
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Show, attend and tell: Neural image caption generation with visual attention
Xu, K., Ba, J., Kiros, R., Courville, A., Salakhutdinov, R., Zemel, R., Bengio, Y.: · 2015
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From captions to visual concepts and back
Fang, H., Gupta, S., Iandola, F., Srivastava, R.K., Deng, L., Dollár, P., Gao, J., He, X., Mitchell, M., Platt, J.C., et al.: · 2015
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Guiding long-short term memory for image caption generation
Jia, X., Gavves, E., Fernando, B., Tuytelaars, T.: · 2015
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Every moment counts: Dense detailed labeling of actions in complex videos
Yeung, S., Russakovsky, O., Jin, N., Andriluka, M., Mori, G., Fei-Fei, L.: · 2015
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Youtube2text: Recognizing and describing arbitrary activities using semantic hierarchies and zero-shot recognition
Guadarrama, S., Krishnamoorthy, N., Malkarnenkar, G., Venugopalan, S., Mooney, R., Darrell, T., Saenko, K.: · 2013
Cited alongside, same era.
Attribute-based classification for zero-shot visual object categorization
Lampert, C., Nickisch, H., Harmeling, S.: · 2013
Cited alongside, same era.
Justification narratives for individual classifications
Biran, O., McKeown, K.: · 2014
Cited alongside, same era.
Multimodal neural language models
Kiros, R., Salakhutdinov, R., Zemel, R.: · 2014
Cited alongside, same era.
Explain images with multimodal recurrent neural networks
Mao, J., Xu, W., Yang, Y., Wang, J., Yuille, A.L.: · 2014
Cited alongside, same era.
Caffe: Convolutional architecture for fast feature embedding
Jia, Y., Shelhamer, E., Donahue, J., Karayev, S., Long, J., Girshick, R., Guadarrama, S., Darrell, T.: · 2014
Cited alongside, same era.
Vedantam, R., Lawrence Zitnick, C., Parikh, D.: · 2015
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Learning like a child: Fast novel visual concept learning from sentence descriptions of images
Mao, J., Wei, X., Yang, Y., Wang, J., Huang, Z., Yuille, A.L.: · 2015
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Compact bilinear pooling
Gao, Y., Beijbom, O., Zhang, N., Darrell, T.: · 2016
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Learning discriminative features via label consistent neural network
Jiang, Z., Wang, Y., Davis, L., Andrews, W., Rozgic, V.: · 2016
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Generation and comprehension of unambiguous object descriptions
Mao, J., Huang, J., Toshev, A., Camburu, O., Yuille, A., Murphy, K.: · 2016
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Learning deep representations of fine-grained visual descriptions
Reed, S., Akata, Z., Lee, H., Schiele, B.: · 2016
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Learning to compose neural networks for question answering
Andreas, J., Rohrbach, M., Darrell, T., Klein, D.: · 2016
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Deep compositional captioning: Describing novel object categories without paired training data
Hendricks, L.A., Venugopalan, S., Rohrbach, M., Mooney, R., Saenko, K., Darrell, T.: · 2016
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