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Auxiliary Learning

Auxiliary learning aims to find or design auxiliary tasks which can improve the performance on one or some primary tasks.

( Image credit: Self-Supervised Generalisation with Meta Auxiliary Learning )

Papers

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Showing 76–100 of 100 papers

TitleStatusHype
HiMAL: A Multimodal Hierarchical Multi-task Auxiliary Learning framework for predicting and explaining Alzheimer disease progression—0
Multimodal Topic-Enriched Auxiliary Learning for Depression Detection—0
Multi-task Collaborative Pre-training and Individual-adaptive-tokens Fine-tuning: A Unified Framework for Brain Representation Learning—0
NeurAll: Towards a Unified Visual Perception Model for Automated Driving—0
Novel Natural Language Summarization of Program Code via Leveraging Multiple Input Representations—0
Pareto Self-Supervised Training for Few-Shot Learning—0
Dataset2Vec: Learning Dataset Meta-FeaturesCode0
Deep Auxiliary Learning for Visual Localization and OdometryCode0
Improving CTC-based speech recognition via knowledge transferring from pre-trained language modelsCode0
Boost-RS: Boosted Embeddings for Recommender Systems and its Application to Enzyme-Substrate Interaction PredictionCode0
When does Self-Prediction help? Understanding Auxiliary Tasks in Reinforcement LearningCode0
Auxiliary Learning by Implicit DifferentiationCode0
On Exploring Pose Estimation as an Auxiliary Learning Task for Visible-Infrared Person Re-identificationCode0
Efficient Multi-Task Auxiliary Learning: Selecting Auxiliary Data by Feature SimilarityCode0
AANG: Automating Auxiliary LearningCode0
Enhancing Deep Knowledge Tracing with Auxiliary TasksCode0
Enhancing Molecular Property Prediction with Auxiliary Learning and Task-Specific AdaptationCode0
Auxiliary Learning for Self-Supervised Video Representation via Similarity-based Knowledge DistillationCode0
Self-Supervised Generalisation with Meta Auxiliary LearningCode0
Learning Object Placements For Relational Instructions by Hallucinating Scene RepresentationsCode0
SGTC: Semantic-Guided Triplet Co-training for Sparsely Annotated Semi-Supervised Medical Image SegmentationCode0
Benchmark for Uncertainty & Robustness in Self-Supervised LearningCode0
SDF-TopoNet: A Two-Stage Framework for Tubular Structure Segmentation via SDF Pre-training and Topology-Aware Fine-TuningCode0
Aux-NAS: Exploiting Auxiliary Labels with Negligibly Extra Inference CostCode0
Auxiliary Tasks and Exploration Enable ObjectNavCode0
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