Discover and Cure: Concept-aware Mitigation of Spurious Correlation
🖥 Github: https://github.com/wuyxin/disc
⏩ Paper: https://arxiv.org/pdf/2305.00650v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/metashift
@ArtificialIntelligencedl
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👍6❤2🔥1
Shotgun crystal structure prediction using machine-learned formation energies
🖥 Github: https://github.com/yoshida-lab/XenonPy/blob/master/samples/CSP_with_element_substitution.ipynb
⏩ Paper: https://arxiv.org/pdf/2305.02158v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/materials-project
@ArtificialIntelligencedl
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Multimodal Data Augmentation for Image Captioning using Diffusion Models
🖥 Github: https://github.com/xiaochr/multimodal-augmentation-image-captioning
⏩ Paper: https://arxiv.org/pdf/2305.01855v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/coco
@ArtificialIntelligencedl
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👍8❤2🔥2
Pre-train and Search: Efficient Embedding Table Sharding with Pre-trained Neural Cost Models
🖥 Github: https://github.com/daochenzha/neuroshard
⏩ Paper: https://arxiv.org/pdf/2305.01868v1.pdf
@ArtificialIntelligencedl
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Towards Being Parameter-Efficient: A Stratified Sparsely Activated Transformer with Dynamic Capacity
🖥 Github: https://github.com/fe1ixxu/stratified_mixture_of_experts
⏩ Paper: https://arxiv.org/pdf/2305.02176v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/flores-200
@ArtificialIntelligencedl
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👍3🔥2❤1
Hybrid and Collaborative Passage Reranking
🖥 Github: https://github.com/zmzhang2000/hybrank
⏩ Paper: https://arxiv.org/pdf/2305.09313v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/natural-questions
@ArtificialIntelligencedl
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❤6🔥2👍1
Dynamic Sparse Training with Structured Sparsity
🖥 Github: https://github.com/calgaryml/condensed-sparsity
⏩ Paper: https://arxiv.org/pdf/2305.02299v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/cifar-10
@ArtificialIntelligencedl
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👍5❤4👎1
Concurrent Misclassification and Out-of-Distribution Detection for Semantic Segmentation via Energy-Based Normalizing Flow
🖥 Github: https://github.com/gudovskiy/flowenedet
⏩ Paper: https://arxiv.org/pdf/2305.09610v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/coco
@ArtificialIntelligencedl
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🔥6👍2❤1
Online Continual Learning Without the Storage Constraint
🖥 Github: https://github.com/drimpossible/acm
⏩ Paper: https://arxiv.org/pdf/2305.09253v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/yfcc100m
@ArtificialIntelligencedl
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👍7🔥2❤1
Pre-Training to Learn in Context
🖥 Github: https://github.com/thu-coai/picl
⏩ Paper: https://arxiv.org/pdf/2305.09137v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/sst
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👍6❤2🔥1
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👍7❤1🥰1
LGTM
🖥 Github: https://github.com/twinkle0331/lgtm
⏩ Paper: https://arxiv.org/pdf/2305.09651v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/sst
@ArtificialIntelligencedl
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👍6🔥2
SSSegmenation
🖥 Github: https://github.com/segmentationblwx/sssegmentation
⏩ Paper: https://arxiv.org/pdf/2305.17091v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/cityscapes
@ArtificialIntelligencedl
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👍8❤1🔥1
Meta-prediction Model for Distillation-Aware NAS on Unseen Datasets
🖥 Github: https://github.com/cownowan/dass
⏩ Paper: https://arxiv.org/pdf/2305.16948v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/cub-200-2011
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👍9❤1🔥1
Occ-BEV: Multi-Camera Unified Pre-training via 3D Scene Reconstruction
🖥 Github: https://github.com/chaytonmin/occ-bev
⏩ Paper: https://arxiv.org/pdf/2305.18829v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/imagenet
@ArtificialIntelligencedl
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👍6🔥1🥰1
Jax OffBench
🖥 Github: https://github.com/sail-sg/offbench
⏩ Paper: https://arxiv.org/pdf/2306.00972v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/d4rl
@ArtificialIntelligencedl
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👍5❤1🔥1
(Almost) Provable Error Bounds Under Distribution Shift via Disagreement Discrepancy
🖥 Github: https://github.com/erosenfeld/disagree_discrep
⏩ Paper: https://arxiv.org/pdf/2306.00312v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/cifar-10
@ArtificialIntelligencedl
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BUOL: A Bottom-Up Framework with Occupancy-aware Lifting for Panoptic 3D Scene Reconstruction From A Single Image
🖥 Github: https://github.com/chtsy/buol
⏩ Paper: https://arxiv.org/pdf/2306.00965v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/matterport3d
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👍6🥰2🔥1
Asymmetric VQGAN
🖥 Github: https://github.com/buxiangzhiren/asymmetric_vqgan
⏩ Paper: https://arxiv.org/pdf/2306.04632v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/imagenet
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👍9❤1🔥1