research
∙
09/19/2023
Differentiable Quantum Architecture Search for Quantum Reinforcement Learning
Differentiable quantum architecture search (DQAS) is a gradient-based fr...
share
research
∙
09/15/2023
Adversarial Attacks on Tables with Entity Swap
The capabilities of large language models (LLMs) have been successfully ...
research
∙
08/22/2023
Multi-event Video-Text Retrieval
Video-Text Retrieval (VTR) is a crucial multi-modal task in an era of ma...
research
∙
08/21/2023
FedDAT: An Approach for Foundation Model Finetuning in Multi-Modal Heterogeneous Federated Learning
Recently, foundation models have exhibited remarkable advancements in mu...
research
∙
08/16/2023
FedPop: Federated Population-based Hyperparameter Tuning
Federated Learning (FL) is a distributed machine learning (ML) paradigm,...
research
∙
07/24/2023
A Systematic Survey of Prompt Engineering on Vision-Language Foundation Models
Prompt engineering is a technique that involves augmenting a large pre-t...
research
∙
07/12/2023
Can Vision-Language Models be a Good Guesser? Exploring VLMs for Times and Location Reasoning
Vision-Language Models (VLMs) are expected to be capable of reasoning wi...
research
∙
06/03/2023
Benchmarking Robustness of Adaptation Methods on Pre-trained Vision-Language Models
Various adaptation methods, such as LoRA, prompts, and adapters, have be...
research
∙
05/26/2023
GRAtt-VIS: Gated Residual Attention for Auto Rectifying Video Instance Segmentation
Recent trends in Video Instance Segmentation (VIS) have seen a growing r...
research
∙
05/15/2023
A Knowledge Graph Perspective on Supply Chain Resilience
Global crises and regulatory developments require increased supply chain...
research
∙
04/02/2023
Improving Few-Shot Inductive Learning on Temporal Knowledge Graphs using Confidence-Augmented Reinforcement Learning
Temporal knowledge graph completion (TKGC) aims to predict the missing l...
research
∙
01/12/2023
Modeling the evolution of temporal knowledge graphs with uncertainty
Forecasting future events is a fundamental challenge for temporal knowle...
research
∙
12/23/2022
Do DALL-E and Flamingo Understand Each Other?
A major goal of multimodal research is to improve machine understanding ...
research
∙
11/19/2022
CL-CrossVQA: A Continual Learning Benchmark for Cross-Domain Visual Question Answering
Visual Question Answering (VQA) is a multi-discipline research task. To ...
research
∙
11/15/2022
Few-Shot Inductive Learning on Temporal Knowledge Graphs using Concept-Aware Information
Knowledge graph completion (KGC) aims to predict the missing links among...
research
∙
09/29/2022
Named Entity Recognition in Industrial Tables using Tabular Language Models
Specialized transformer-based models for encoding tabular data have gain...
research
∙
08/22/2022
InstanceFormer: An Online Video Instance Segmentation Framework
Recent transformer-based offline video instance segmentation (VIS) appro...
research
∙
08/12/2022
Forecasting Question Answering over Temporal Knowledge Graphs
Question answering over temporal knowledge graphs (TKGQA) has recently f...
research
∙
07/25/2022
SegPGD: An Effective and Efficient Adversarial Attack for Evaluating and Boosting Segmentation Robustness
Deep neural network-based image classifications are vulnerable to advers...
research
∙
06/13/2022
Biologically Inspired Neural Path Finding
The human brain can be considered to be a graphical structure comprising...
research
∙
06/03/2022
On Calibration of Graph Neural Networks for Node Classification
Graphs can model real-world, complex systems by representing entities an...
research
∙
05/31/2022
Continuous Temporal Graph Networks for Event-Based Graph Data
There has been an increasing interest in modeling continuous-time dynami...
research
∙
05/30/2022
FRAug: Tackling Federated Learning with Non-IID Features via Representation Augmentation
Federated Learning (FL) is a decentralized learning paradigm in which mu...
research
∙
05/21/2022
Learning Meta Representations of One-shot Relations for Temporal Knowledge Graph Link Prediction
Few-shot relational learning for static knowledge graphs (KGs) has drawn...
research
∙
03/19/2022
Relationformer: A Unified Framework for Image-to-Graph Generation
A comprehensive representation of an image requires understanding object...
research
∙
03/17/2022
Enhanced Temporal Knowledge Embeddings with Contextualized Language Representations
With the emerging research effort to integrate structured and unstructur...
research
∙
12/15/2021
TLogic: Temporal Logical Rules for Explainable Link Forecasting on Temporal Knowledge Graphs
Conventional static knowledge graphs model entities in relational data a...
research
∙
12/14/2021
A Simple But Powerful Graph Encoder for Temporal Knowledge Graph Completion
While knowledge graphs contain rich semantic knowledge of various entiti...
research
∙
11/22/2021
Adversarial Examples on Segmentation Models Can be Easy to Transfer
Deep neural network-based image classification can be misled by adversar...
research
∙
11/20/2021
Are Vision Transformers Robust to Patch Perturbations?
The recent advances in Vision Transformer (ViT) have demonstrated its im...
research
∙
10/28/2021
Generating Table Vector Representations
High-quality Web tables are rich sources of information that can be used...
research
∙
09/27/2021
The Tensor Brain: A Unified Theory of Perception, Memory and Semantic Decoding
We present a unified computational theory of perception and memory. In o...
research
∙
09/24/2021
Description-based Label Attention Classifier for Explainable ICD-9 Classification
ICD-9 coding is a relevant clinical billing task, where unstructured tex...
research
∙
08/10/2021
Adaptive Multi-Resolution Attention with Linear Complexity
Transformers have improved the state-of-the-art across numerous tasks in...
research
∙
08/03/2021
Categorical EHR Imputation with Generative Adversarial Nets
Electronic Health Records often suffer from missing data, which poses a ...
research
∙
07/26/2021
Uncertainty-Aware Time-to-Event Prediction using Deep Kernel Accelerated Failure Time Models
Recurrent neural network based solutions are increasingly being used in ...
research
∙
07/19/2021
OODformer: Out-Of-Distribution Detection Transformer
A serious problem in image classification is that a trained model might ...
research
∙
07/13/2021
Graphhopper: Multi-Hop Scene Graph Reasoning for Visual Question Answering
Visual Question Answering (VQA) is concerned with answering free-form qu...
research
∙
07/12/2021
Scenes and Surroundings: Scene Graph Generation using Relation Transformer
Identifying objects in an image and their mutual relationships as a scen...
research
∙
07/10/2021
Improving Inductive Link Prediction Using Hyper-Relational Facts
For many years, link prediction on knowledge graphs (KGs) has been a pur...
research
∙
06/01/2021
Quantifying Predictive Uncertainty in Medical Image Analysis with Deep Kernel Learning
Deep neural networks are increasingly being used for the analysis of med...
research
∙
03/29/2021
Capsule Network is Not More Robust than Convolutional Network
The Capsule Network is widely believed to be more robust than Convolutio...
research
∙
03/18/2021
Neural Multi-Hop Reasoning With Logical Rules on Biomedical Knowledge Graphs
Biomedical knowledge graphs permit an integrative computational approach...
research
∙
03/05/2021
NF-GNN: Network Flow Graph Neural Networks for Malware Detection and Classification
Malicious software (malware) poses an increasing threat to the security ...
research
∙
02/19/2021
Effective and Efficient Vote Attack on Capsule Networks
Standard Convolutional Neural Networks (CNNs) can be easily fooled by im...
research
∙
02/09/2021
Improving Visual Reasoning by Exploiting The Knowledge in Texts
This paper presents a new framework for training image-based classifiers...
research
∙
01/13/2021
Temporal Knowledge Graph Forecasting with Neural ODE
Learning node representation on dynamically-evolving, multi-relational g...
research
∙
12/31/2020
xERTE: Explainable Reasoning on Temporal Knowledge Graphs for Forecasting Future Links
Interest has been rising lately towards modeling time-evolving knowledge...
research
∙
12/03/2020
Interpretable Graph Capsule Networks for Object Recognition
Capsule Networks, as alternatives to Convolutional Neural Networks, have...
research
∙
11/19/2020