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07/20/2023
The Role of Entropy and Reconstruction in Multi-View Self-Supervised Learning
The mechanisms behind the success of multi-view self-supervised learning...
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06/01/2023
FigGen: Text to Scientific Figure Generation
The generative modeling landscape has experienced tremendous growth in r...
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02/10/2023
Long-Context Language Decision Transformers and Exponential Tilt for Interactive Text Environments
Text-based game environments are challenging because agents must deal wi...
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12/13/2022
3rd Continual Learning Workshop Challenge on Egocentric Category and Instance Level Object Understanding
Continual Learning, also known as Lifelong or Incremental Learning, has ...
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10/19/2022
OCR-VQGAN: Taming Text-within-Image Generation
Synthetic image generation has recently experienced significant improvem...
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10/13/2022
MAPL: Parameter-Efficient Adaptation of Unimodal Pre-Trained Models for Vision-Language Few-Shot Prompting
Large pre-trained models have proved to be remarkable zero- and (prompt-...
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10/04/2022
CADet: Fully Self-Supervised Anomaly Detection With Contrastive Learning
Handling out-of-distribution (OOD) samples has become a major stake in t...
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08/30/2022
Constraining Representations Yields Models That Know What They Don't Know
A well-known failure mode of neural networks corresponds to high confide...
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07/10/2022
Scaling the Number of Tasks in Continual Learning
Standard gradient descent algorithms applied to sequences of tasks are k...
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05/24/2022
Workflow Discovery from Dialogues in the Low Data Regime
Text-based dialogues are now widely used to solve real-world problems. I...
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04/30/2022
Foundational Models for Continual Learning: An Empirical Study of Latent Replay
Rapid development of large-scale pre-training has resulted in foundation...
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04/05/2022
Data Augmentation for Intent Classification with Off-the-shelf Large Language Models
Data augmentation is a widely employed technique to alleviate the proble...
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03/30/2022
Challenges in leveraging GANs for few-shot data augmentation
In this paper, we explore the use of GAN-based few-shot data augmentatio...
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11/23/2021
Multi-label Iterated Learning for Image Classification with Label Ambiguity
Transfer learning from large-scale pre-trained models has become essenti...
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11/15/2021
Continual Learning via Local Module Composition
Modularity is a compelling solution to continual learning (CL), the prob...
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10/27/2021
A Survey of Self-Supervised and Few-Shot Object Detection
Labeling data is often expensive and time-consuming, especially for task...
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08/21/2021
SSR: Semi-supervised Soft Rasterizer for single-view 2D to 3D Reconstruction
Recent work has made significant progress in learning object meshes with...
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08/02/2021
Sequoia: A Software Framework to Unify Continual Learning Research
The field of Continual Learning (CL) seeks to develop algorithms that ac...
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04/14/2021
Can Active Learning Preemptively Mitigate Fairness Issues?
Dataset bias is one of the prevailing causes of unfairness in machine le...
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03/30/2021
Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Data
Remote sensing and automatic earth monitoring are key to solve global-sc...
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03/18/2021
Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations
Explainability for machine learning models has gained considerable atten...
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12/08/2020
Hierarchical Residual Attention Network for Single Image Super-Resolution
Convolutional neural networks are the most successful models in single i...
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11/14/2020
Counting Cows: Tracking Illegal Cattle Ranching From High-Resolution Satellite Imagery
Cattle farming is responsible for 8.8% of greenhouse gas emissions world...
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11/06/2020
Affinity LCFCN: Learning to Segment Fish with Weak Supervision
Aquaculture industries rely on the availability of accurate fish body me...
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09/14/2020
Synbols: Probing Learning Algorithms with Synthetic Datasets
Progress in the field of machine learning has been fueled by the introdu...
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09/14/2020
CVPR 2020 Continual Learning in Computer Vision Competition: Approaches, Results, Current Challenges and Future Directions
In the last few years, we have witnessed a renewed and fast-growing inte...
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08/05/2020
OverNet: Lightweight Multi-Scale Super-Resolution with Overscaling Network
Super-resolution (SR) has achieved great success due to the development ...
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07/04/2020
A Weakly Supervised Consistency-based Learning Method for COVID-19 Segmentation in CT Images
Acquiring count annotations generally requires less human effort than po...
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07/03/2020
LOOC: Localize Overlapping Objects with Count Supervision
Acquiring count annotations generally requires less human effort than po...
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03/12/2020
Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning
Learning from non-stationary data remains a great challenge for machine ...
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03/09/2020
Embedding Propagation: Smoother Manifold for Few-Shot Classification
Few-shot classification is challenging because the data distribution of ...
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07/19/2018
Attend and Rectify: a Gated Attention Mechanism for Fine-Grained Recovery
We propose a novel attention mechanism to enhance Convolutional Neural N...
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06/28/2018
Beyond One-hot Encoding: lower dimensional target embedding
Target encoding plays a central role when learning Convolutional Neural ...
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05/23/2018
TADAM: Task dependent adaptive metric for improved few-shot learning
Few-shot learning has become essential for producing models that general...
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02/06/2018
Deep Inference of Personality Traits by Integrating Image and Word Use in Social Networks
Social media, as a major platform for communication and information exch...
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11/07/2016
