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Generating visual explanations with natural language

https://doi.org/10.1002/ail2.55
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-030-01216-8_17openalex-snapshot
Grounding Visual Explanations
inferredcites →https://doi.org/10.1007/978-3-319-46493-0_1openalex-snapshot
Generating Visual Explanations
inferredcites →https://doi.org/10.1007/bf00992696openalex-snapshot
Simple statistical gradient-following algorithms for connectionist reinforcement learning
inferredcites →https://doi.org/10.1007/s11263-016-0981-7openalex-snapshot
Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations
inferredcites →https://doi.org/10.1016/0010-4809(81)90012-4openalex-snapshot
An analysis of physician attitudes regarding computer-based clinical consultation systems
inferredcites →https://doi.org/10.1016/0025-5564(75)90047-4openalex-snapshot
A model of inexact reasoning in medicine
inferredcites →https://doi.org/10.1016/j.artint.2018.07.007openalex-snapshot
Explanation in artificial intelligence: Insights from the social sciences
inferredcites →https://doi.org/10.1016/j.tics.2006.08.004openalex-snapshot
The structure and function of explanations
inferredcites →https://doi.org/10.1017/s026988890200019xopenalex-snapshot
A review of explanation methods for Bayesian networks
inferredcites →https://doi.org/10.1093/oxfordhb/9780199734689.013.0014openalex-snapshot
Explanation and Abductive Inference
inferredcites →https://doi.org/10.1109/cvpr.2015.7298754openalex-snapshot
From captions to visual concepts and back
inferredcites →https://doi.org/10.1109/cvpr.2015.7298878openalex-snapshot
Long-term recurrent convolutional networks for visual recognition and description
inferredcites →https://doi.org/10.1109/cvpr.2015.7298932openalex-snapshot
Deep visual-semantic alignments for generating image descriptions
inferredcites →https://doi.org/10.1109/cvpr.2015.7298935openalex-snapshot
Show and tell: A neural image caption generator
inferredcites →https://doi.org/10.1109/cvpr.2015.7299087openalex-snapshot
CIDEr: Consensus-based image description evaluation
inferredcites →https://doi.org/10.1109/cvpr.2016.13openalex-snapshot
Learning Deep Representations of Fine-Grained Visual Descriptions
inferredcites →https://doi.org/10.1109/cvpr.2016.41openalex-snapshot
Compact Bilinear Pooling
inferredcites →https://doi.org/10.1109/cvpr.2017.131openalex-snapshot
Self-Critical Sequence Training for Image Captioning
inferredcites →https://doi.org/10.1109/cvpr.2017.334openalex-snapshot
Top-Down Visual Saliency Guided by Captions
inferredcites →https://doi.org/10.1109/cvpr.2017.354openalex-snapshot
Network Dissection: Quantifying Interpretability of Deep Visual Representations
inferredcites →https://doi.org/10.1109/cvpr.2017.470openalex-snapshot
Modeling Relationships in Referential Expressions with Compositional Modular Networks
inferredcites →https://doi.org/10.1109/cvpr.2018.00915openalex-snapshot
Multimodal Explanations: Justifying Decisions and Pointing to the Evidence
inferredcites →https://doi.org/10.1109/iccv.2015.277openalex-snapshot
Guiding the Long-Short Term Memory Model for Image Caption Generation
inferredcites →https://doi.org/10.1109/iccv.2017.74openalex-snapshot
Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization
inferredcites →https://doi.org/10.1109/tpami.2012.162openalex-snapshot
BabyTalk: Understanding and Generating Simple Image Descriptions
inferredcites →https://doi.org/10.1109/tpami.2016.2598339openalex-snapshot
Deep Visual-Semantic Alignments for Generating Image Descriptions
inferredcites →https://doi.org/10.1145/2157689.2157748openalex-snapshot
Explaining robot actions
inferredcites →https://doi.org/10.1145/3065386openalex-snapshot
ImageNet classification with deep convolutional neural networks
inferredcites →https://doi.org/10.1162/neco.1997.9.8.1735openalex-snapshot
Long Short-Term Memory
inferredcites →https://doi.org/10.18653/v1/d18-1128openalex-snapshot
Do explanations make VQA models more predictable to a human?
inferredcites →https://doi.org/10.21236/ada459166openalex-snapshot
Building Explainable Artificial Intelligence Systems
inferredcites →https://doi.org/10.48550/arxiv.1309.6855openalex-snapshot
Evaluating computational models of explanation using human judgments
inferredcites →https://doi.org/10.48550/arxiv.1310.1531openalex-snapshot
DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition
inferredcites →https://doi.org/10.48550/arxiv.1409.1556openalex-snapshot
Very Deep Convolutional Networks for Large-Scale Image Recognition
inferredcites →https://doi.org/10.48550/arxiv.1412.6632openalex-snapshot
Deep Captioning with Multimodal Recurrent Neural Networks (m-RNN)
inferredcites →https://doi.org/10.48550/arxiv.1502.03044openalex-snapshot
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1002/ail2.61openalex-snapshot
DARPA 's explainable AI ( XAI ) program: A retrospective
inferred← citeshttps://doi.org/10.1002/jeo2.12039openalex-snapshot
A practical guide to the implementation of AI in orthopaedic research, Part 6: How to evaluate the performance of AI research?
inferred← citeshttps://doi.org/10.1007/978-3-031-73242-3_18openalex-snapshot
GazeXplain: Learning to Predict Natural Language Explanations of Visual Scanpaths
inferred← citeshttps://doi.org/10.1109/ethics65148.2025.11098293openalex-snapshot
Transparent AI Without Deception, Limitation, and Guidance
inferred← citeshttps://doi.org/10.1109/tfuzz.2024.3425664openalex-snapshot
VL-MFER: A Vision-Language Multimodal Pretrained Model With Multiway-Fuzzy-Experts Bidirectional Retention Network
inferred← citeshttps://doi.org/10.1145/3641022openalex-snapshot
The Impact of Imperfect XAI on Human-AI Decision-Making
inferred← citeshttps://doi.org/10.1145/3687056openalex-snapshot
The Explanation That Hits Home: The Characteristics of Verbal Explanations That Affect Human Perception in Subjective Decision-Making
inferred← citeshttps://doi.org/10.1145/3750052openalex-snapshot
Imperfections of XAI: Phenomena Influencing AI-Assisted Decision-Making
inferred← citeshttps://doi.org/10.17586/2226-1494-2025-25-3-373-386openalex-snapshot
Explainability and interpretability are important aspects in ensuring the security of decisions made by intelligent systems (review article)
inferred← citeshttps://doi.org/10.3390/ai4030033openalex-snapshot
Explainable Image Classification: The Journey So Far and the Road Ahead
inferred← citeshttps://doi.org/10.3390/app14167192openalex-snapshot
The Effect of Communicating AI Confidence on Human Decision Making When Performing a Binary Decision Task
inferred← citeshttps://doi.org/10.5465/amr.2020.0205openalex-snapshot
Competitive Advantage Through Artificial Intelligence: Toward a Theory of Situated AI
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