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09/08/2023
AMLP:Adaptive Masking Lesion Patches for Self-supervised Medical Image Segmentation
Self-supervised masked image modeling has shown promising results on nat...
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08/15/2023
Brain-Inspired Computational Intelligence via Predictive Coding
Artificial intelligence (AI) is rapidly becoming one of the key technolo...
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08/05/2023
NP-SemiSeg: When Neural Processes meet Semi-Supervised Semantic Segmentation
Semi-supervised semantic segmentation involves assigning pixel-wise labe...
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06/27/2023
Causal Inference via Predictive Coding
Bayesian and causal inference are fundamental processes for intelligence...
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06/26/2023
Minimum Description Length Clustering to Measure Meaningful Image Complexity
Existing image complexity metrics cannot distinguish meaningful content ...
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06/06/2023
An Empirical Analysis of Parameter-Efficient Methods for Debiasing Pre-Trained Language Models
The increasingly large size of modern pretrained language models not onl...
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06/02/2023
Evaluating Language Models for Mathematics through Interactions
The standard methodology of evaluating large language models (LLMs) base...
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05/29/2023
Faithfulness Tests for Natural Language Explanations
Explanations of neural models aim to reveal a model's decision-making pr...
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04/15/2023
MvCo-DoT:Multi-View Contrastive Domain Transfer Network for Medical Report Generation
In clinical scenarios, multiple medical images with different views are ...
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04/07/2023
Machine Learning with Requirements: a Manifesto
In the recent years, machine learning has made great advancements that h...
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04/05/2023
Correcting Flaws in Common Disentanglement Metrics
Recent years have seen growing interest in learning disentangled represe...
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03/29/2023
Hard Regularization to Prevent Collapse in Online Deep Clustering without Data Augmentation
Online deep clustering refers to the joint use of a feature extraction n...
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02/27/2023
MPS-AMS: Masked Patches Selection and Adaptive Masking Strategy Based Self-Supervised Medical Image Segmentation
Existing self-supervised learning methods based on contrastive learning ...
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02/22/2023
Multi-Head Feature Pyramid Networks for Breast Mass Detection
Analysis of X-ray images is one of the main tools to diagnose breast can...
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02/11/2023
Counter-GAP: Counterfactual Bias Evaluation through Gendered Ambiguous Pronouns
Bias-measuring datasets play a critical role in detecting biased behavio...
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01/31/2023
Mathematical Capabilities of ChatGPT
We investigate the mathematical capabilities of ChatGPT by testing it on...
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01/31/2023
NP-Match: Towards a New Probabilistic Model for Semi-Supervised Learning
Semi-supervised learning (SSL) has been widely explored in recent years,...
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01/15/2023
Rationalizing Predictions by Adversarial Information Calibration
Explaining the predictions of AI models is paramount in safety-critical ...
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12/09/2022
Robust Graph Representation Learning via Predictive Coding
Predictive coding is a message-passing framework initially developed to ...
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11/14/2022
Learning to Model Multimodal Semantic Alignment for Story Visualization
Story visualization aims to generate a sequence of images to narrate eac...
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10/04/2022
ROAD-R: The Autonomous Driving Dataset with Logical Requirements
Neural networks have proven to be very powerful at computer vision tasks...
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09/17/2022
Efficient Deep Clustering of Human Activities and How to Improve Evaluation
There has been much recent research on human activity recognition (HA...
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09/08/2022
Lightweight Long-Range Generative Adversarial Networks
In this paper, we introduce novel lightweight generative adversarial net...
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08/15/2022
Memory-Driven Text-to-Image Generation
We introduce a memory-driven semi-parametric approach to text-to-image g...
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08/03/2022
Word-Level Fine-Grained Story Visualization
Story visualization aims to generate a sequence of images to narrate eac...
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07/24/2022
PCA: Semi-supervised Segmentation with Patch Confidence Adversarial Training
Deep learning based semi-supervised learning (SSL) methods have achieved...
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07/09/2022
Explaining Chest X-ray Pathologies in Natural Language
Most deep learning algorithms lack explanations for their predictions, w...
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07/03/2022
NP-Match: When Neural Processes meet Semi-Supervised Learning
Semi-supervised learning (SSL) has been widely explored in recent years,...
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06/18/2022
Rethinking Bayesian Deep Learning Methods for Semi-Supervised Volumetric Medical Image Segmentation
Recently, several Bayesian deep learning methods have been proposed for ...
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05/01/2022
Deep Learning with Logical Constraints
In recent years, there has been an increasing interest in exploiting log...
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01/07/2022
The Defeat of the Winograd Schema Challenge
The Winograd Schema Challenge – a set of twin sentences involving pronou...
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12/12/2021
Few-Shot Out-of-Domain Transfer Learning of Natural Language Explanations
Recently, there has been an increasing interest in models that generate ...
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11/15/2021
Rationale production to support clinical decision-making
The development of neural networks for clinical artificial intelligence ...
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08/30/2021
Knowledge Base Completion Meets Transfer Learning
The aim of knowledge base completion is to predict unseen facts from exi...
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08/15/2021
Accurate, yet inconsistent? Consistency Analysis on Language Understanding Models
Consistency, which refers to the capability of generating the same predi...
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07/22/2021
Selective Pseudo-label Clustering
Deep neural networks (DNNs) offer a means of addressing the challenging ...
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06/25/2021
Rationale-Inspired Natural Language Explanations with Commonsense
Explainable machine learning models primarily justify predicted labels u...
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06/18/2021
RSG: A Simple but Effective Module for Learning Imbalanced Datasets
Imbalanced datasets widely exist in practice and area great challenge fo...
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05/23/2021
Controlling Text Edition by Changing Answers of Specific Questions
In this paper, we introduce the new task of controllable text edition, i...
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05/08/2021
e-ViL: A Dataset and Benchmark for Natural Language Explanations in Vision-Language Tasks
Recently, an increasing number of works have introduced models capable o...
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03/24/2021
Multi-Label Classification Neural Networks with Hard Logical Constraints
Multi-label classification (MC) is a standard machine learning problem i...
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12/16/2020
Learning from the Best: Rationalizing Prediction by Adversarial Information Calibration
Explaining the predictions of AI models is paramount in safety-critical ...
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12/16/2020
Multi-type Disentanglement without Adversarial Training
Controlling the style of natural language by disentangling the latent sp...
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11/16/2020
Reinforced Medical Report Generation with X-Linear Attention and Repetition Penalty
To reduce doctors' workload, deep-learning-based automatic medical repor...
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11/15/2020
SAG-GAN: Semi-Supervised Attention-Guided GANs for Data Augmentation on Medical Images
Recently deep learning methods, in particular, convolutional neural netw...
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11/03/2020
The Gap on GAP: Tackling the Problem of Differing Data Distributions in Bias-Measuring Datasets
Diagnostic datasets that can detect biased models are an important prere...
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11/02/2020
Deep Learning in Computer-Aided Diagnosis and Treatment of Tumors: A Survey
Computer-Aided Diagnosis and Treatment of Tumors is a hot topic of deep ...
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10/23/2020
Lightweight Generative Adversarial Networks for Text-Guided Image Manipulation
We propose a novel lightweight generative adversarial network for effici...
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10/20/2020
Coherent Hierarchical Multi-Label Classification Networks
Hierarchical multi-label classification (HMC) is a challenging classific...
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10/06/2020