Papers + Code
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Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions
Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions
Attacking Visual Language Grounding with Adversarial Examples: A Case Study on Neural Image Captioning.
Attacking Visual Language Grounding with Adversarial Examples: A Case Study on Neural Image Captioning.
Attacking Visual Language Grounding with Adversarial Examples: A Case Study on Neural Image Captioning
Attacking Visual Language Grounding with Adversarial Examples: A Case Study on Neural Image Captioning
Learning to Teach in Cooperative Multiagent Reinforcement Learning
Learning to Teach in Cooperative Multiagent Reinforcement Learning
Jointly Optimize Data Augmentation and Network Training: Adversarial Data Augmentation in Human Pose Estimation
Jointly Optimize Data Augmentation and Network Training: Adversarial Data Augmentation in Human Pose Estimation
AutoZOOM: Autoencoder-based Zeroth Order Optimization Method for Attacking Black-box Neural Networks
AutoZOOM: Autoencoder-based Zeroth Order Optimization Method for Attacking Black-box Neural Networks
Delta-encoder: an effective sample synthesis method for few-shot object recognition
Delta-encoder: an effective sample synthesis method for few-shot object recognition
Geometry Guided Convolutional Neural Networks for Self-Supervised Video Representation Learning
Geometry Guided Convolutional Neural Networks for Self-Supervised Video Representation Learning
Structured Adversarial Attack: Towards General Implementation and Better Interpretability
Structured Adversarial Attack: Towards General Implementation and Better Interpretability
Controllable Image-to-Video Translation: A Case Study on Facial Expression Generation
Controllable Image-to-Video Translation: A Case Study on Facial Expression Generation
emrQA: A Large Corpus for Question Answering on Electronic Medical Records
emrQA: A Large Corpus for Question Answering on Electronic Medical Records
Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders
Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders
Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding
Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding
MiME: Multilevel Medical Embedding of Electronic Health Records for Predictive Healthcare
MiME: Multilevel Medical Embedding of Electronic Health Records for Predictive Healthcare
GAN Dissection: Visualizing and Understanding Generative Adversarial Networks
GAN Dissection: Visualizing and Understanding Generative Adversarial Networks
CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks
CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks
MAi : An Intelligent Model Acquisition Interface for Interactive Specification of Dialogue Agents
MAi : An Intelligent Model Acquisition Interface for Interactive Specification of Dialogue Agents
Moments in Time Dataset: one million videos for event understanding
Moments in Time Dataset: one million videos for event understanding
Structural Supervision Improves Learning of Non-Local Grammatical Dependencies
Structural Supervision Improves Learning of Non-Local Grammatical Dependencies
The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision
The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision
Imposing Label-Relational Inductive Bias for Extremely Fine-Grained Entity Typing
Imposing Label-Relational Inductive Bias for Extremely Fine-Grained Entity Typing
Beyond RNNs: Positional Self-Attention with Co-Attention for Video Question Answering
Beyond RNNs: Positional Self-Attention with Co-Attention for Video Question Answering
Neural language models as psycholinguistic subjects: Representations of syntactic state
Neural language models as psycholinguistic subjects: Representations of syntactic state
Evaluating the Interpretability of the Knowledge Compilation Map: Communicating Logical Statements Effectively
Evaluating the Interpretability of the Knowledge Compilation Map: Communicating Logical Statements Effectively
The Algonauts Project: A Platform for Communication between the Sciences of Biological and Artificial Intelligence
The Algonauts Project: A Platform for Communication between the Sciences of Biological and Artificial Intelligence
Learning to Learn without Forgetting By Maximizing Transfer and Minimizing Interference
Learning to Learn without Forgetting By Maximizing Transfer and Minimizing Interference
Selection Bias Explorations and Debias Methods for Natural Language Sentence Matching Datasets
Selection Bias Explorations and Debias Methods for Natural Language Sentence Matching Datasets
SimVAE: Simulator-Assisted Training for Interpretable Generative Models
SimVAE: Simulator-Assisted Training for Interpretable Generative Models
Class-wise rationalization: teaching AI to weigh pros and cons
Class-wise rationalization: teaching AI to weigh pros and cons
Topics are more meaningful than words. AI for comparative literature.
Topics are more meaningful than words. AI for comparative literature.
ObjectNet: A large-scale bias-controlled dataset for pushing the limits of object recognition models
ObjectNet: A large-scale bias-controlled dataset for pushing the limits of object recognition models
Characterization and Learning of Causal Graphs with Latent Variables from Soft Interventions
Characterization and Learning of Causal Graphs with Latent Variables from Soft Interventions
Scalable Spike Source Localization in Extracellular Recordings using Amortized Variational Inference
Scalable Spike Source Localization in Extracellular Recordings using Amortized Variational Inference
CAG: A Real-Time Low-Cost Enhanced-Robustness High-Transferability Content-Aware Adversarial Attack Generator
CAG: A Real-Time Low-Cost Enhanced-Robustness High-Transferability Content-Aware Adversarial Attack Generator
Online AI planning with graph neural networks and adaptive scheduling
Online AI planning with graph neural networks and adaptive scheduling
Sentence Embedding Alignment for Lifelong Relation Extraction
Sentence Embedding Alignment for Lifelong Relation Extraction
Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics
Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics
On the Design of Black-box Adversarial Examples by Leveraging Gradient-free Optimization and Operator Splitting Method
On the Design of Black-box Adversarial Examples by Leveraging Gradient-free Optimization and Operator Splitting Method
LaSO: Label-Set Operations networks for multi-label few-shot learning
LaSO: Label-Set Operations networks for multi-label few-shot learning
RepMet: Representative-based metric learning for classification and one-shot object detection
RepMet: Representative-based metric learning for classification and one-shot object detection
Experiences and Insights for Collaborative Industry-Academic Research in Artificial Intelligence
Experiences and Insights for Collaborative Industry-Academic Research in Artificial Intelligence
Relationship Matters: Relation Guided Knowledge Transfer for Incremental Learning of Object Detectors
Relationship Matters: Relation Guided Knowledge Transfer for Incremental Learning of Object Detectors
Min-Max Optimization without Gradients: Convergence and Applications to Black-Box Evasion and Poisoning Attacks
Min-Max Optimization without Gradients: Convergence and Applications to Black-Box Evasion and Poisoning Attacks
Gaussian-Smoothed Optimal Transport: Metric Structure and Statistical Efficiency
Gaussian-Smoothed Optimal Transport: Metric Structure and Statistical Efficiency
We Have So Much in Common: Modeling Semantic Relational Set Abstractions in Videos
We Have So Much in Common: Modeling Semantic Relational Set Abstractions in Videos
AdaShare: Learning What To Share For Efficient Deep Multi-Task Learning
AdaShare: Learning What To Share For Efficient Deep Multi-Task Learning
Log-Likelihood Ratio Minimizing Flows: Towards Robust and Quantifiable Neural Distribution Alignment
Log-Likelihood Ratio Minimizing Flows: Towards Robust and Quantifiable Neural Distribution Alignment
Simulating a Primary Visual Cortex at the Front of CNNs Improves Robustness to Image Perturbations
Simulating a Primary Visual Cortex at the Front of CNNs Improves Robustness to Image Perturbations
Asymptotic Guarantees for Generative Modeling based on the Smooth Wasserstein Distance
Asymptotic Guarantees for Generative Modeling based on the Smooth Wasserstein Distance
Causal Discovery from Soft Interventions with Unknown Targets: Characterization and Learning
Causal Discovery from Soft Interventions with Unknown Targets: Characterization and Learning
Simulating a Primary Visual Cortex at the Front of CNNs Improves Robustness to Image Perturbations
Simulating a Primary Visual Cortex at the Front of CNNs Improves Robustness to Image Perturbations
Learning Neural-Symbolic Descriptive Planning Models via Cube-Space Priors: The Voyage Home (to STRIPS)
Learning Neural-Symbolic Descriptive Planning Models via Cube-Space Priors: The Voyage Home (to STRIPS)
A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning
A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning
Narrative Question Answering with Cutting-Edge Open-Domain QA Techniques: A Comprehensive Study
Narrative Question Answering with Cutting-Edge Open-Domain QA Techniques: A Comprehensive Study
Benchmarking Commercial Intent Detection Services with Practice-Driven Evaluations
Benchmarking Commercial Intent Detection Services with Practice-Driven Evaluations
Interactive Fiction Game Playing as Multi-Paragraph Reading Comprehension with Reinforcement Learning
Interactive Fiction Game Playing as Multi-Paragraph Reading Comprehension with Reinforcement Learning
Auto-NBA: Efficient and Effective Search Over The Joint Space of Networks, Bitwidths, and Accelerators
Auto-NBA: Efficient and Effective Search Over The Joint Space of Networks, Bitwidths, and Accelerators
Complementary Evidence Identification in Open-Domain Question Answering
Complementary Evidence Identification in Open-Domain Question Answering
Augmenting Policy Learning with Routines Discovered from a Single Demonstration
Augmenting Policy Learning with Routines Discovered from a Single Demonstration
RSPNet: Relative Speed Perception for Unsupervised Video Representation Learning.
RSPNet: Relative Speed Perception for Unsupervised Video Representation Learning.
Grounding Physical Concepts of Objects and Events Through Dynamic Visual Reasoning
Grounding Physical Concepts of Objects and Events Through Dynamic Visual Reasoning
Neural Network Control Policy Verification with Persistent Adversarial Perturbations
Neural Network Control Policy Verification with Persistent Adversarial Perturbations
The Lottery Tickets Hypothesis for Supervised and Self-supervised Pre-training in Computer Vision Models
The Lottery Tickets Hypothesis for Supervised and Self-supervised Pre-training in Computer Vision Models
Found a Reason for me? Weakly-supervised Grounded Visual Question Answering using Capsules
Found a Reason for me? Weakly-supervised Grounded Visual Question Answering using Capsules
High-Dimensional Feature Selection for Sample Efficient Treatment Effect Estimation
High-Dimensional Feature Selection for Sample Efficient Treatment Effect Estimation
A Deep Reinforcement Learning Approach to First-Order Logic Theorem Proving
A Deep Reinforcement Learning Approach to First-Order Logic Theorem Proving
RT3D: Achieving Real-Time Execution of 3D Convolutional Neural Networks on Mobile Devices
RT3D: Achieving Real-Time Execution of 3D Convolutional Neural Networks on Mobile Devices
Heterogeneous Knowledge Transfer via Hierarchical Teaching in Cooperative Multiagent Reinforcement Learning
Heterogeneous Knowledge Transfer via Hierarchical Teaching in Cooperative Multiagent Reinforcement Learning
Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors
Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors
Understanding Behavior of Clinical Models under Domain Shifts
Understanding Behavior of Clinical Models under Domain Shifts
Fashion IQ: A New Dataset towards Retrieving Images by Natural Language Feedback
Fashion IQ: A New Dataset towards Retrieving Images by Natural Language Feedback
StarNet: towards weakly supervised few-shot detection and explainable few-shot classification
StarNet: towards weakly supervised few-shot detection and explainable few-shot classification
HAT: Hardware-Aware Transformers for Efficient Natural Language Processing
HAT: Hardware-Aware Transformers for Efficient Natural Language Processing
Camera On-boarding for Person Re-identification using Hypothesis Transfer Learning
Camera On-boarding for Person Re-identification using Hypothesis Transfer Learning
NASTransfer: Analyzing Architecture Transferability in Large Scale Neural Architecture Search
NASTransfer: Analyzing Architecture Transferability in Large Scale Neural Architecture Search
An Image Enhancing Pattern-based Sparsity for Real-time Inference on Mobile Devices
An Image Enhancing Pattern-based Sparsity for Real-time Inference on Mobile Devices
Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport
Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport
Graph Universal Adversarial Attacks: A Few Bad Actors Ruin Graph Learning Models
Graph Universal Adversarial Attacks: A Few Bad Actors Ruin Graph Learning Models
Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case
Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case
Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using Mismatched Hypothesis Testing
Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using Mismatched Hypothesis Testing
Spoken Moments: Learning Joint Audio-Visual Representations from Video Descriptions
Spoken Moments: Learning Joint Audio-Visual Representations from Video Descriptions
Deep Analysis of CNN-based Spatio-temporal Representations for Action Recognition
Deep Analysis of CNN-based Spatio-temporal Representations for Action Recognition
A Targeted Assessment of Incremental Processing in Neural Language Models and Humans
A Targeted Assessment of Incremental Processing in Neural Language Models and Humans
On Sample Based Explanation Methods for NLP: Efficiency, Faithfulness, and Semantic Evaluation
On Sample Based Explanation Methods for NLP: Efficiency, Faithfulness, and Semantic Evaluation
MSRP Industry Night: Career Exploration with IBM
MSRP Industry Night: Career Exploration with IBM
Decentralized Learning for Overparameterized Problems: A Multi-Agent Kernel Approximation Approach
Decentralized Learning for Overparameterized Problems: A Multi-Agent Kernel Approximation Approach
FALCON: Fast Visual Concept Learning by Integrating Images, Linguistic descriptions, and Conceptual Relations
FALCON: Fast Visual Concept Learning by Integrating Images, Linguistic descriptions, and Conceptual Relations
The Algonauts Project 2021 Challenge: How the Human Brain Makes Sense of a World in Motion
The Algonauts Project 2021 Challenge: How the Human Brain Makes Sense of a World in Motion
Tune It the Right Way: Unsupervised Validation of Domain Adaptation via Soft Neighborhood Density
Tune It the Right Way: Unsupervised Validation of Domain Adaptation via Soft Neighborhood Density
Generalized and Incremental Few-Shot Learning by Explicit Learning and Calibration without Forgetting
Generalized and Incremental Few-Shot Learning by Explicit Learning and Calibration without Forgetting
Multi-Moments in Time: Learning and Interpreting Models for Multi-Action Video Understanding
Multi-Moments in Time: Learning and Interpreting Models for Multi-Action Video Understanding
How Do Neural Sequence Models Generalize? Local and Global Cues for Out-of-Distribution Prediction
How Do Neural Sequence Models Generalize? Local and Global Cues for Out-of-Distribution Prediction
Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks
Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks
When does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning?
When does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning?
Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Sparse Neural Networks
Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Sparse Neural Networks
Look at What I’m Doing: Self-Supervised Spatial Grounding of Narrations in Instructional Videos
Look at What I’m Doing: Self-Supervised Spatial Grounding of Narrations in Instructional Videos
PerSim: Data-Efficient Offline Reinforcement Learning with Heterogeneous Agents via Personalized Simulators
PerSim: Data-Efficient Offline Reinforcement Learning with Heterogeneous Agents via Personalized Simulators
Tailoring: encoding inductive biases by optimizing unsupervised objectives at prediction time
Tailoring: encoding inductive biases by optimizing unsupervised objectives at prediction time
Understanding End-to-End Model-Based Reinforcement Learning Methods as Implicit Parameterization
Understanding End-to-End Model-Based Reinforcement Learning Methods as Implicit Parameterization
GLIB: Efficient Exploration for Relational Model-Based Reinforcement Learning via Goal-Literal Babbling
GLIB: Efficient Exploration for Relational Model-Based Reinforcement Learning via Goal-Literal Babbling
A Class of Geometric Structures in Transfer Learning: Minimax Bounds and Optimality
A Class of Geometric Structures in Transfer Learning: Minimax Bounds and Optimality
DiffSkill: Skill Abstraction from Differentiable Physics for Deformable Object Manipulations with Tools
DiffSkill: Skill Abstraction from Differentiable Physics for Deformable Object Manipulations with Tools
RISP: Rendering-Invariant State Predictor with Differentiable Simulation and Rendering for Cross-Domain Parameter Estimation
RISP: Rendering-Invariant State Predictor with Differentiable Simulation and Rendering for Cross-Domain Parameter Estimation
How unlabeled data improve generalization in self-training? A one-hidden-layer theoretical analysis
How unlabeled data improve generalization in self-training? A one-hidden-layer theoretical analysis
Beyond Worst-Case Analysis in Stochastic Approximation: Moment Estimation Improves Instance Complexity
Beyond Worst-Case Analysis in Stochastic Approximation: Moment Estimation Improves Instance Complexity
Revisiting Contrastive Learning through the Lens of Neighborhood Component Analysis: an Integrated Framework
Revisiting Contrastive Learning through the Lens of Neighborhood Component Analysis: an Integrated Framework
Music Gesture for Visual Sound Separation
Music Gesture for Visual Sound Separation
How hard are computer vision datasets? Calibrating dataset difficulty to viewing time
How hard are computer vision datasets? Calibrating dataset difficulty to viewing time
Fair Infinitesimal Jackknife: Mitigating the Influence of Biased Training Data Points Without Refitting
Fair Infinitesimal Jackknife: Mitigating the Influence of Biased Training Data Points Without Refitting
Bringing Image Scene Structure to Video via Frame-Clip Consistency of Object Tokens
Bringing Image Scene Structure to Video via Frame-Clip Consistency of Object Tokens
Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks
Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks
Convergent representations of computer programs in human and artificial neural networks
Convergent representations of computer programs in human and artificial neural networks
Finding Differences Between Transformers and ConvNets Using Counterfactual Simulation Testing
Finding Differences Between Transformers and ConvNets Using Counterfactual Simulation Testing
S3-NeRF: Neural Reflectance Field from Shading and Shadow under a Single Viewpoint
S3-NeRF: Neural Reflectance Field from Shading and Shadow under a Single Viewpoint
Losses Can Be Blessings: Routing Self-Supervised Speech Representations Towards Efficient Multilingual and Multitask Speech Processing
Losses Can Be Blessings: Routing Self-Supervised Speech Representations Towards Efficient Multilingual and Multitask Speech Processing
Proximal Stochastic Recursive Momentum Methods for Nonconvex Composite Decentralized Optimization
Proximal Stochastic Recursive Momentum Methods for Nonconvex Composite Decentralized Optimization
Minimum-Entropy Coupling Approximation Guarantees Beyond the Majorization Barrier
Minimum-Entropy Coupling Approximation Guarantees Beyond the Majorization Barrier
A Theoretical Understanding of Shallow Vision Transformers: Learning, Generalization, and Sample Complexity
A Theoretical Understanding of Shallow Vision Transformers: Learning, Generalization, and Sample Complexity
Aligning Model and Macaque Inferior Temporal Cortex Representations Improves Model-to-Human Behavioral Alignment and Adversarial Robustness
Aligning Model and Macaque Inferior Temporal Cortex Representations Improves Model-to-Human Behavioral Alignment and Adversarial Robustness
DexDeform: Dexterous Deformable Object Manipulation with Human Demonstrations and Differentiable Physics
DexDeform: Dexterous Deformable Object Manipulation with Human Demonstrations and Differentiable Physics
PAC-NeRF: Physics Augmented Continuum Neural Radiance Fields for Geometry-Agnostic System Identification
PAC-NeRF: Physics Augmented Continuum Neural Radiance Fields for Geometry-Agnostic System Identification
CODA-Prompt: COntinual Decomposed Attention-based Prompting for Rehearsal-Free Continual Learning
CODA-Prompt: COntinual Decomposed Attention-based Prompting for Rehearsal-Free Continual Learning
Compressed Decentralized Proximal Stochastic Gradient Method for Nonconvex Composite Problems with Heterogeneous Data
Compressed Decentralized Proximal Stochastic Gradient Method for Nonconvex Composite Problems with Heterogeneous Data
ConCerNet: A Contrastive Learning Based Framework for Automated Conservation Law Discovery and Trustworthy Dynamical System Prediction
ConCerNet: A Contrastive Learning Based Framework for Automated Conservation Law Discovery and Trustworthy Dynamical System Prediction