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03/09/2023
PDSketch: Integrated Planning Domain Programming and Learning
This paper studies a model learning and online planning approach towards...
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03/09/2023
On the Expressiveness and Generalization of Hypergraph Neural Networks
This extended abstract describes a framework for analyzing the expressiv...
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03/30/2022
FALCON: Fast Visual Concept Learning by Integrating Images, Linguistic descriptions, and Conceptual Relations
We present a meta-learning framework for learning new visual concepts qu...
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02/17/2022
Grammar-Based Grounded Lexicon Learning
We present Grammar-Based Grounded Lexicon Learning (G2L2), a lexicalist ...
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06/10/2021
Temporal and Object Quantification Networks
We present Temporal and Object Quantification Networks (TOQ-Nets), a new...
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04/22/2021
Hierarchical Motion Understanding via Motion Programs
Current approaches to video analysis of human motion focus on raw pixels...
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03/30/2021
Grounding Physical Concepts of Objects and Events Through Dynamic Visual Reasoning
We study the problem of dynamic visual reasoning on raw videos. This is ...
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12/31/2020
Language-Mediated, Object-Centric Representation Learning
We present Language-mediated, Object-centric Representation Learning (LO...
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12/21/2020
Object-Centric Diagnosis of Visual Reasoning
When answering questions about an image, it not only needs knowing what ...
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11/19/2020
Multi-Plane Program Induction with 3D Box Priors
We consider two important aspects in understanding and editing images: m...
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06/25/2020
Perspective Plane Program Induction from a Single Image
We study the inverse graphics problem of inferring a holistic representa...
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02/04/2020
Visual Concept-Metaconcept Learning
Humans reason with concepts and metaconcepts: we recognize red and green...
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09/04/2019
Program-Guided Image Manipulators
Humans are capable of building holistic representations for images at va...
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06/17/2019
Neurally-Guided Structure Inference
Most structure inference methods either rely on exhaustive search or are...
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06/07/2019
Visually Grounded Neural Syntax Acquisition
We present the Visually Grounded Neural Syntax Learner (VG-NSL), an appr...
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04/26/2019
Neural Logic Machines
We propose the Neural Logic Machine (NLM), a neural-symbolic architectur...
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04/26/2019
The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision
We propose the Neuro-Symbolic Concept Learner (NS-CL), a model that lear...
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04/11/2019
Unified Visual-Semantic Embeddings: Bridging Vision and Language with Structured Meaning Representations
We propose the Unified Visual-Semantic Embeddings (Unified VSE) for lear...
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04/11/2019
UniVSE: Robust Visual Semantic Embeddings via Structured Semantic Representations
We propose Unified Visual-Semantic Embeddings (UniVSE) for learning a jo...
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11/06/2018
Neural Phrase-to-Phrase Machine Translation
In this paper, we propose Neural Phrase-to-Phrase Machine Translation (N...
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07/30/2018
Acquisition of Localization Confidence for Accurate Object Detection
Modern CNN-based object detectors rely on bounding box regression and no...
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06/27/2018
Learning Visually-Grounded Semantics from Contrastive Adversarial Samples
We study the problem of grounding distributional representations of text...
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05/08/2017
