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EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 25 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 12 -
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 38 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 19
Collections
Discover the best community collections!
Collections including paper arxiv:2402.19479
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LocalMamba: Visual State Space Model with Windowed Selective Scan
Paper • 2403.09338 • Published • 7 -
GiT: Towards Generalist Vision Transformer through Universal Language Interface
Paper • 2403.09394 • Published • 25 -
Panda-70M: Captioning 70M Videos with Multiple Cross-Modality Teachers
Paper • 2402.19479 • Published • 32 -
Grounding DINO 1.5: Advance the "Edge" of Open-Set Object Detection
Paper • 2405.10300 • Published • 26
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The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 602 -
MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases
Paper • 2402.14905 • Published • 126 -
YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information
Paper • 2402.13616 • Published • 45 -
Panda-70M: Captioning 70M Videos with Multiple Cross-Modality Teachers
Paper • 2402.19479 • Published • 32
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The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 602 -
Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models
Paper • 2402.17177 • Published • 88 -
Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models
Paper • 2402.19427 • Published • 52 -
Panda-70M: Captioning 70M Videos with Multiple Cross-Modality Teachers
Paper • 2402.19479 • Published • 32
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The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 602 -
GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection
Paper • 2403.03507 • Published • 182 -
Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models
Paper • 2402.19427 • Published • 52 -
ResLoRA: Identity Residual Mapping in Low-Rank Adaption
Paper • 2402.18039 • Published • 11
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Aria Everyday Activities Dataset
Paper • 2402.13349 • Published • 29 -
YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information
Paper • 2402.13616 • Published • 45 -
Panda-70M: Captioning 70M Videos with Multiple Cross-Modality Teachers
Paper • 2402.19479 • Published • 32 -
Evaluating D-MERIT of Partial-annotation on Information Retrieval
Paper • 2406.16048 • Published • 34
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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 21 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 80 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 143 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
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LLaMA Beyond English: An Empirical Study on Language Capability Transfer
Paper • 2401.01055 • Published • 54 -
Improving Text Embeddings with Large Language Models
Paper • 2401.00368 • Published • 79 -
HyperLLaVA: Dynamic Visual and Language Expert Tuning for Multimodal Large Language Models
Paper • 2403.13447 • Published • 18 -
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Paper • 2403.05530 • Published • 60