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[1] Yishay Mansour,et al. Policy Gradient Methods for Reinforcement Learning with Function Approximation , 1999, NIPS.
[2] Ronald J. Williams,et al. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning , 2004, Machine Learning.
[3] Li Fei-Fei,et al. ImageNet: A large-scale hierarchical image database , 2009, CVPR.
[4] Afsaneh Fazly,et al. A Probabilistic Computational Model of Cross-Situational Word Learning , 2010, Cogn. Sci..
[5] Luke S. Zettlemoyer,et al. Weakly Supervised Learning of Semantic Parsers for Mapping Instructions to Actions , 2013, TACL.
[6] Yoshua Bengio,et al. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation , 2014, EMNLP.
[7] Ruslan Salakhutdinov,et al. Unifying Visual-Semantic Embeddings with Multimodal Neural Language Models , 2014, ArXiv.
[8] Pietro Perona,et al. Microsoft COCO: Common Objects in Context , 2014, ECCV.
[9] Mario Fritz,et al. A Multi-World Approach to Question Answering about Real-World Scenes based on Uncertain Input , 2014, NIPS.
[10] Jeffrey Pennington,et al. GloVe: Global Vectors for Word Representation , 2014, EMNLP.
[11] Sanja Fidler,et al. Aligning Books and Movies: Towards Story-Like Visual Explanations by Watching Movies and Reading Books , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[12] Li Fei-Fei,et al. Generating Semantically Precise Scene Graphs from Textual Descriptions for Improved Image Retrieval , 2015, VL@EMNLP.
[13] Scott E. Reed,et al. Weakly-supervised Disentangling with Recurrent Transformations for 3D View Synthesis , 2015, NIPS.
[14] Grzegorz Chrupala,et al. Learning language through pictures , 2015, ACL.
[15] Lisa Anne Hendricks,et al. Long-term recurrent convolutional networks for visual recognition and description , 2015, CVPR.
[16] Joshua B. Tenenbaum,et al. Deep Convolutional Inverse Graphics Network , 2015, NIPS.
[17] Jiasen Lu,et al. VQA: Visual Question Answering , 2015, ICCV.
[18] Michael S. Bernstein,et al. Image retrieval using scene graphs , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[19] Wei Xu,et al. ABC-CNN: An Attention Based Convolutional Neural Network for Visual Question Answering , 2015, ArXiv.
[20] Kate Saenko,et al. Ask, Attend and Answer: Exploring Question-Guided Spatial Attention for Visual Question Answering , 2015, ECCV.
[21] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[22] Alexander J. Smola,et al. Stacked Attention Networks for Image Question Answering , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[23] Allan Jabri,et al. Revisiting Visual Question Answering Baselines , 2016, ECCV.
[24] Sanja Fidler,et al. Order-Embeddings of Images and Language , 2015, ICLR.
[25] Mirella Lapata,et al. Language to Logical Form with Neural Attention , 2016, ACL.
[26] Dan Klein,et al. Learning to Compose Neural Networks for Question Answering , 2016, NAACL.
[27] Alan L. Yuille,et al. Training and Evaluating Multimodal Word Embeddings with Large-scale Web Annotated Images , 2016, NIPS.
[28] Li Fei-Fei,et al. DenseCap: Fully Convolutional Localization Networks for Dense Captioning , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[29] Razvan Pascanu,et al. A simple neural network module for relational reasoning , 2017, NIPS.
[30] Chen Sun,et al. VQS: Linking Segmentations to Questions and Answers for Supervised Attention in VQA and Question-Focused Semantic Segmentation , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[31] Li Fei-Fei,et al. CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[32] Frank D. Wood,et al. Learning Disentangled Representations with Semi-Supervised Deep Generative Models , 2017, NIPS.
[33] Li Fei-Fei,et al. Inferring and Executing Programs for Visual Reasoning , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[34] Honglak Lee,et al. Zero-Shot Task Generalization with Multi-Task Deep Reinforcement Learning , 2017, ICML.
[35] Nathaniel J. Smith,et al. Bootstrapping language acquisition , 2017, Cognition.
[36] Yann Dauphin,et al. Convolutional Sequence to Sequence Learning , 2017, ICML.
[37] Abhinav Gupta,et al. What's in a Question: Using Visual Questions as a Form of Supervision , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[38] Demis Hassabis,et al. SCAN: Learning Abstract Hierarchical Compositional Visual Concepts , 2017, ArXiv.
[39] Jiajun Wu,et al. Neural Scene De-rendering , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[40] Justin Johnson,et al. DDRprog: A CLEVR Differentiable Dynamic Reasoning Programmer , 2018, ArXiv.
[41] Christopher D. Manning,et al. Compositional Attention Networks for Machine Reasoning , 2018, ICLR.
[42] Yuning Jiang,et al. Learning Visually-Grounded Semantics from Contrastive Adversarial Samples , 2018, COLING.
[43] Christian Wolf,et al. Object Level Visual Reasoning in Videos , 2018, ECCV.
[44] Aaron C. Courville,et al. FiLM: Visual Reasoning with a General Conditioning Layer , 2017, AAAI.
[45] Chuang Gan,et al. Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding , 2018, NeurIPS.
[46] Lei Zhang,et al. Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[47] Leslie Pack Kaelbling,et al. From Skills to Symbols: Learning Symbolic Representations for Abstract High-Level Planning , 2018, J. Artif. Intell. Res..
[48] Trevor Darrell,et al. Explainable Neural Computation via Stack Neural Module Networks , 2018, ECCV.
[49] David Mascharka,et al. Transparency by Design: Closing the Gap Between Performance and Interpretability in Visual Reasoning , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[50] Roger Levy,et al. Word learning and the acquisition of syntactic-semantic overhypotheses , 2018, CogSci.