Artificial Intelligence
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Artificial Intelligence

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Towards Being Parameter-Efficient: A Stratified Sparsely Activated Transformer with Dynamic Capacity

πŸ–₯ Github: https://github.com/fe1ixxu/stratified_mixture_of_experts

⏩ Paper: https://arxiv.org/pdf/2305.02176v1.pdf

πŸ’¨ Dataset: https://paperswithcode.com/dataset/flores-200

@ArtificialIntelligencedl
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Concurrent Misclassification and Out-of-Distribution Detection for Semantic Segmentation via Energy-Based Normalizing Flow

πŸ–₯ Github: https://github.com/gudovskiy/flowenedet

⏩ Paper: https://arxiv.org/pdf/2305.09610v1.pdf

πŸ’¨ Dataset: https://paperswithcode.com/dataset/coco

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Online Continual Learning Without the Storage Constraint

πŸ–₯ Github: https://github.com/drimpossible/acm

⏩ Paper: https://arxiv.org/pdf/2305.09253v1.pdf

πŸ’¨ Dataset: https://paperswithcode.com/dataset/yfcc100m

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Meta-prediction Model for Distillation-Aware NAS on Unseen Datasets

πŸ–₯ Github: https://github.com/cownowan/dass

⏩ Paper: https://arxiv.org/pdf/2305.16948v1.pdf

πŸ’¨ Dataset: https://paperswithcode.com/dataset/cub-200-2011

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Occ-BEV: Multi-Camera Unified Pre-training via 3D Scene Reconstruction

πŸ–₯ Github: https://github.com/chaytonmin/occ-bev

⏩ Paper: https://arxiv.org/pdf/2305.18829v1.pdf

πŸ’¨ Dataset: https://paperswithcode.com/dataset/imagenet

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(Almost) Provable Error Bounds Under Distribution Shift via Disagreement Discrepancy

πŸ–₯ Github: https://github.com/erosenfeld/disagree_discrep

⏩ Paper: https://arxiv.org/pdf/2306.00312v1.pdf

πŸ’¨ Dataset: https://paperswithcode.com/dataset/cifar-10

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BUOL: A Bottom-Up Framework with Occupancy-aware Lifting for Panoptic 3D Scene Reconstruction From A Single Image

πŸ–₯ Github: https://github.com/chtsy/buol

⏩ Paper: https://arxiv.org/pdf/2306.00965v1.pdf

πŸ’¨ Dataset: https://paperswithcode.com/dataset/matterport3d

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Galactic: Scaling End-to-End Reinforcement Learning for Rearrangement
at 100k Steps-Per-Second


πŸ–₯ Github: https://github.com/facebookresearch/galactic

⏩ Paper: https://arxiv.org/pdf/2306.07552v1.pdf

πŸ’¨ Dataset: https://paperswithcode.com/dataset/vizdoom

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Semi-supervised learning made simple with self-supervised clustering [CVPR 2023]

πŸ–₯ Github: https://github.com/pietroastolfi/suave-daino

⏩ Paper: https://arxiv.org/pdf/2306.07483v1.pdf

πŸ’¨ Dataset: https://paperswithcode.com/dataset/imagenet

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Semi-supervised learning made simple with self-supervised clustering [CVPR 2023]

πŸ–₯ Github: https://github.com/Ruixinhua/ExplainableNRS

⏩ Paper: https://arxiv.org/pdf/2306.07506v1.pdf

πŸ’¨ Dataset: https://paperswithcode.com/dataset/mind

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LabelBench: A Comprehensive Framework for Benchmarking Label-Efficient Learning

πŸ–₯ Github: https://github.com/efficienttraining/labelbench

⏩ Paper: https://arxiv.org/pdf/2306.09910v1.pdf

πŸ’¨ Dataset: https://paperswithcode.com/dataset/cifar-10

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