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09/20/2023
Retrieve-Rewrite-Answer: A KG-to-Text Enhanced LLMs Framework for Knowledge Graph Question Answering
Despite their competitive performance on knowledge-intensive tasks, larg...
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07/02/2023
Morse Neural Networks for Uncertainty Quantification
We introduce a new deep generative model useful for uncertainty quantifi...
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06/20/2023
The Bayesian Regularized Quantile Varying Coefficient Model
The quantile varying coefficient (VC) model can flexibly capture dynamic...
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06/05/2023
Inflated 3D Convolution-Transformer for Weakly-supervised Carotid Stenosis Grading with Ultrasound Videos
Localization of the narrowest position of the vessel and corresponding v...
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05/26/2023
Building One-class Detector for Anything: Open-vocabulary Zero-shot OOD Detection Using Text-image Models
We focus on the challenge of out-of-distribution (OOD) detection in deep...
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05/25/2023
DiffusionShield: A Watermark for Copyright Protection against Generative Diffusion Models
Recently, Generative Diffusion Models (GDMs) have showcased their remark...
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05/24/2023
Sharpness-Aware Data Poisoning Attack
Recent research has highlighted the vulnerability of Deep Neural Network...
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04/30/2023
Second-order Anisotropic Gaussian Directional Derivative Filters for Blob Detection
Interest point detection methods have received increasing attention and ...
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04/17/2023
On Uncertainty Calibration and Selective Generation in Probabilistic Neural Summarization: A Benchmark Study
Modern deep models for summarization attains impressive benchmark perfor...
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02/19/2023
Rethinking Memory Profiling and Migration for Multi-Tiered Large Memory Systems
Multi-tiered large memory systems call for rethinking of memory profilin...
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02/13/2023
A Simple Zero-shot Prompt Weighting Technique to Improve Prompt Ensembling in Text-Image Models
Contrastively trained text-image models have the remarkable ability to p...
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12/20/2022
Improving the Robustness of Summarization Models by Detecting and Removing Input Noise
The evaluation of abstractive summarization models typically uses test d...
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10/18/2022
Transferable Unlearnable Examples
With more people publishing their personal data online, unauthorized dat...
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10/17/2022
Probabilistic Categorical Adversarial Attack Adversarial Training
The existence of adversarial examples brings huge concern for people to ...
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09/30/2022
Out-of-Distribution Detection and Selective Generation for Conditional Language Models
Machine learning algorithms typically assume independent and identically...
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09/13/2022
Exemplar-Based Image Colorization with A Learning Framework
Image learning and colorization are hot spots in multimedia domain. Insp...
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08/22/2022
Sequential Circuits Synthesis for Rapid Single Flux Quantum Logic Based on Finite State Machine Decomposition
Rapid Single Flux Quantum (RSFQ) logic is a promising technology to supe...
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08/16/2022
Color Image Edge Detection using Multi-scale and Multi-directional Gabor filter
In this paper, a color edge detection method is proposed where the multi...
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07/24/2022
Proving Common Mechanisms Shared by Twelve Methods of Boosting Adversarial Transferability
Although many methods have been proposed to enhance the transferability ...
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06/01/2022
Defense Against Gradient Leakage Attacks via Learning to Obscure Data
Federated learning is considered as an effective privacy-preserving lear...
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05/27/2022
A Hybrid Josephson Transmission Line and Passive Transmission Line Routing Framework for Single Flux Quantum Logic
The Single Flux Quantum (SFQ) logic family is a novel digital logic as i...
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05/18/2022
Pluralistic Image Completion with Probabilistic Mixture-of-Experts
Pluralistic image completion focuses on generating both visually realist...
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05/04/2022
Towards Theoretical Analysis of Transformation Complexity of ReLU DNNs
This paper aims to theoretically analyze the complexity of feature trans...
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05/01/2022
A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness
Accurate uncertainty quantification is a major challenge in deep learnin...
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02/26/2022
Exploring the Impact of Negative Samples of Contrastive Learning: A Case Study of Sentence Embedding
Contrastive learning is emerging as a powerful technique for extracting ...
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01/24/2022
DrugOOD: Out-of-Distribution (OOD) Dataset Curator and Benchmark for AI-aided Drug Discovery – A Focus on Affinity Prediction Problems with Noise Annotations
AI-aided drug discovery (AIDD) is gaining increasing popularity due to i...
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12/02/2021
MegBA: A High-Performance and Distributed Library for Large-Scale Bundle Adjustment
Large-scale Bundle Adjustment (BA) is the key for many 3D vision applica...
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12/02/2021
Trap of Feature Diversity in the Learning of MLPs
In this paper, we discover a two-phase phenomenon in the learning of mul...
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11/11/2021
Towards Axiomatic, Hierarchical, and Symbolic Explanation for Deep Models
This paper proposes a hierarchical and symbolic And-Or graph (AOG) to ob...
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11/05/2021
A Unified Game-Theoretic Interpretation of Adversarial Robustness
This paper provides a unified view to explain different adversarial atta...
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10/20/2021
ESOD:Edge-based Task Scheduling for Object Detection
Object Detection on the mobile system is a challenge in terms of everyth...
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10/05/2021
Cellular Network Radio Propagation Modeling with Deep Convolutional Neural Networks
Radio propagation modeling and prediction is fundamental for modern cell...
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07/18/2021
Sparse group variable selection for gene-environment interactions in the longitudinal study
Penalized variable selection for high dimensional longitudinal data has ...
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06/30/2021
Sawtooth Factorial Topic Embeddings Guided Gamma Belief Network
Hierarchical topic models such as the gamma belief network (GBN) have de...
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06/21/2021
A Game-Theoretic Taxonomy of Visual Concepts in DNNs
In this paper, we rethink how a DNN encodes visual concepts of different...
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06/16/2021
A Simple Fix to Mahalanobis Distance for Improving Near-OOD Detection
Mahalanobis distance (MD) is a simple and popular post-processing method...
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06/07/2021
Uncertainty Baselines: Benchmarks for Uncertainty Robustness in Deep Learning
High-quality estimates of uncertainty and robustness are crucial for num...
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06/06/2021
Exploring the Limits of Out-of-Distribution Detection
Near out-of-distribution detection (OOD) is a major challenge for deep n...
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05/22/2021
Learning Baseline Values for Shapley Values
This paper aims to formulate the problem of estimating the optimal basel...
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04/19/2021
Probabilistic Mixture-of-Experts for Efficient Deep Reinforcement Learning
Deep reinforcement learning (DRL) has successfully solved various proble...
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04/12/2021
Learning to Remove: Towards Isotropic Pre-trained BERT Embedding
Pre-trained language models such as BERT have become a more common choic...
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04/08/2021
Does Your Dermatology Classifier Know What It Doesn't Know? Detecting the Long-Tail of Unseen Conditions
We develop and rigorously evaluate a deep learning based system that can...
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04/04/2021
Uniting Heterogeneity, Inductiveness, and Efficiency for Graph Representation Learning
With the ubiquitous graph-structured data in various applications, model...
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03/12/2021
Game-theoretic Understanding of Adversarially Learned Features
This paper aims to understand adversarial attacks and defense from a new...
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02/23/2021
Identifying Gene-environment interactions with robust marginal Bayesian variable selection
In high-throughput genetics studies, an important aim is to identify gen...
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01/18/2021
ZeRO-Offload: Democratizing Billion-Scale Model Training
Large-scale model training has been a playing ground for a limited few r...
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10/08/2020
A Unified Approach to Interpreting and Boosting Adversarial Transferability
In this paper, we use the interaction inside adversarial perturbations t...
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07/10/2020
Revisiting One-vs-All Classifiers for Predictive Uncertainty and Out-of-Distribution Detection in Neural Networks
Accurate estimation of predictive uncertainty in modern neural networks ...
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06/29/2020
Interpreting and Disentangling Feature Components of Various Complexity from DNNs
This paper aims to define, quantify, and analyze the feature complexity ...
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06/09/2020