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CatLIP: CLIP-level Visual Recognition Accuracy with 2.7x Faster Pre-training on Web-scale Image-Text Data
Paper • 2404.15653 • Published • 28 -
MoDE: CLIP Data Experts via Clustering
Paper • 2404.16030 • Published • 13 -
MoRA: High-Rank Updating for Parameter-Efficient Fine-Tuning
Paper • 2405.12130 • Published • 49 -
Reducing Transformer Key-Value Cache Size with Cross-Layer Attention
Paper • 2405.12981 • Published • 33
Collections
Discover the best community collections!
Collections including paper arxiv:2410.23287
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SAM 2: Segment Anything in Images and Videos
Paper • 2408.00714 • Published • 123 -
Rethinking Open-Vocabulary Segmentation of Radiance Fields in 3D Space
Paper • 2408.07416 • Published • 7 -
SMITE: Segment Me In TimE
Paper • 2410.18538 • Published • 15 -
ReferEverything: Towards Segmenting Everything We Can Speak of in Videos
Paper • 2410.23287 • Published • 19
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EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 31 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 15 -
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 45 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 24
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FrugalNeRF: Fast Convergence for Few-shot Novel View Synthesis without Learned Priors
Paper • 2410.16271 • Published • 84 -
Baichuan Alignment Technical Report
Paper • 2410.14940 • Published • 51 -
SAM2Long: Enhancing SAM 2 for Long Video Segmentation with a Training-Free Memory Tree
Paper • 2410.16268 • Published • 70 -
AutoTrain: No-code training for state-of-the-art models
Paper • 2410.15735 • Published • 60
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CatLIP: CLIP-level Visual Recognition Accuracy with 2.7x Faster Pre-training on Web-scale Image-Text Data
Paper • 2404.15653 • Published • 28 -
MoDE: CLIP Data Experts via Clustering
Paper • 2404.16030 • Published • 13 -
MoRA: High-Rank Updating for Parameter-Efficient Fine-Tuning
Paper • 2405.12130 • Published • 49 -
Reducing Transformer Key-Value Cache Size with Cross-Layer Attention
Paper • 2405.12981 • Published • 33
-
CatLIP: CLIP-level Visual Recognition Accuracy with 2.7x Faster Pre-training on Web-scale Image-Text Data
Paper • 2404.15653 • Published • 28 -
MoDE: CLIP Data Experts via Clustering
Paper • 2404.16030 • Published • 13 -
MoRA: High-Rank Updating for Parameter-Efficient Fine-Tuning
Paper • 2405.12130 • Published • 49 -
Reducing Transformer Key-Value Cache Size with Cross-Layer Attention
Paper • 2405.12981 • Published • 33
-
FrugalNeRF: Fast Convergence for Few-shot Novel View Synthesis without Learned Priors
Paper • 2410.16271 • Published • 84 -
Baichuan Alignment Technical Report
Paper • 2410.14940 • Published • 51 -
SAM2Long: Enhancing SAM 2 for Long Video Segmentation with a Training-Free Memory Tree
Paper • 2410.16268 • Published • 70 -
AutoTrain: No-code training for state-of-the-art models
Paper • 2410.15735 • Published • 60
-
SAM 2: Segment Anything in Images and Videos
Paper • 2408.00714 • Published • 123 -
Rethinking Open-Vocabulary Segmentation of Radiance Fields in 3D Space
Paper • 2408.07416 • Published • 7 -
SMITE: Segment Me In TimE
Paper • 2410.18538 • Published • 15 -
ReferEverything: Towards Segmenting Everything We Can Speak of in Videos
Paper • 2410.23287 • Published • 19
-
CatLIP: CLIP-level Visual Recognition Accuracy with 2.7x Faster Pre-training on Web-scale Image-Text Data
Paper • 2404.15653 • Published • 28 -
MoDE: CLIP Data Experts via Clustering
Paper • 2404.16030 • Published • 13 -
MoRA: High-Rank Updating for Parameter-Efficient Fine-Tuning
Paper • 2405.12130 • Published • 49 -
Reducing Transformer Key-Value Cache Size with Cross-Layer Attention
Paper • 2405.12981 • Published • 33
-
EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 31 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 15 -
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 45 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 24