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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:2410.00907
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Revisit Large-Scale Image-Caption Data in Pre-training Multimodal Foundation Models
Paper • 2410.02740 • Published • 54 -
From Code to Correctness: Closing the Last Mile of Code Generation with Hierarchical Debugging
Paper • 2410.01215 • Published • 39 -
Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Multimodal Models
Paper • 2409.17146 • Published • 123 -
EuroLLM: Multilingual Language Models for Europe
Paper • 2409.16235 • Published • 29
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RetrievalAttention: Accelerating Long-Context LLM Inference via Vector Retrieval
Paper • 2409.10516 • Published • 43 -
Measuring and Enhancing Trustworthiness of LLMs in RAG through Grounded Attributions and Learning to Refuse
Paper • 2409.11242 • Published • 7 -
Promptriever: Instruction-Trained Retrievers Can Be Prompted Like Language Models
Paper • 2409.11136 • Published • 23 -
On the Diagram of Thought
Paper • 2409.10038 • Published • 13
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Addition is All You Need for Energy-efficient Language Models
Paper • 2410.00907 • Published • 151 -
Emu3: Next-Token Prediction is All You Need
Paper • 2409.18869 • Published • 99 -
An accurate detection is not all you need to combat label noise in web-noisy datasets
Paper • 2407.05528 • Published • 3 -
Is It Really Long Context if All You Need Is Retrieval? Towards Genuinely Difficult Long Context NLP
Paper • 2407.00402 • Published • 22
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Attention Heads of Large Language Models: A Survey
Paper • 2409.03752 • Published • 92 -
Transformer Explainer: Interactive Learning of Text-Generative Models
Paper • 2408.04619 • Published • 175 -
Addition is All You Need for Energy-efficient Language Models
Paper • 2410.00907 • Published • 151 -
DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining
Paper • 2305.10429 • Published • 5
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LinFusion: 1 GPU, 1 Minute, 16K Image
Paper • 2409.02097 • Published • 34 -
Phidias: A Generative Model for Creating 3D Content from Text, Image, and 3D Conditions with Reference-Augmented Diffusion
Paper • 2409.11406 • Published • 27 -
Diffusion Models Are Real-Time Game Engines
Paper • 2408.14837 • Published • 127 -
Segment Anything with Multiple Modalities
Paper • 2408.09085 • Published • 22
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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
-
Addition is All You Need for Energy-efficient Language Models
Paper • 2410.00907 • Published • 151 -
Emu3: Next-Token Prediction is All You Need
Paper • 2409.18869 • Published • 99 -
An accurate detection is not all you need to combat label noise in web-noisy datasets
Paper • 2407.05528 • Published • 3 -
Is It Really Long Context if All You Need Is Retrieval? Towards Genuinely Difficult Long Context NLP
Paper • 2407.00402 • Published • 22
-
Revisit Large-Scale Image-Caption Data in Pre-training Multimodal Foundation Models
Paper • 2410.02740 • Published • 54 -
From Code to Correctness: Closing the Last Mile of Code Generation with Hierarchical Debugging
Paper • 2410.01215 • Published • 39 -
Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Multimodal Models
Paper • 2409.17146 • Published • 123 -
EuroLLM: Multilingual Language Models for Europe
Paper • 2409.16235 • Published • 29
-
Attention Heads of Large Language Models: A Survey
Paper • 2409.03752 • Published • 92 -
Transformer Explainer: Interactive Learning of Text-Generative Models
Paper • 2408.04619 • Published • 175 -
Addition is All You Need for Energy-efficient Language Models
Paper • 2410.00907 • Published • 151 -
DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining
Paper • 2305.10429 • Published • 5
-
RetrievalAttention: Accelerating Long-Context LLM Inference via Vector Retrieval
Paper • 2409.10516 • Published • 43 -
Measuring and Enhancing Trustworthiness of LLMs in RAG through Grounded Attributions and Learning to Refuse
Paper • 2409.11242 • Published • 7 -
Promptriever: Instruction-Trained Retrievers Can Be Prompted Like Language Models
Paper • 2409.11136 • Published • 23 -
On the Diagram of Thought
Paper • 2409.10038 • Published • 13
-
LinFusion: 1 GPU, 1 Minute, 16K Image
Paper • 2409.02097 • Published • 34 -
Phidias: A Generative Model for Creating 3D Content from Text, Image, and 3D Conditions with Reference-Augmented Diffusion
Paper • 2409.11406 • Published • 27 -
Diffusion Models Are Real-Time Game Engines
Paper • 2408.14837 • Published • 127 -
Segment Anything with Multiple Modalities
Paper • 2408.09085 • Published • 22