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Collections including paper arxiv:2410.15735

EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters

Paper • 2402.04252 • Published Feb 6, 2024 • 29
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models

Paper • 2402.03749 • Published Feb 6, 2024 • 14
ScreenAI: A Vision-Language Model for UI and Infographics Understanding

Paper • 2402.04615 • Published Feb 7, 2024 • 44
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss

Paper • 2402.05008 • Published Feb 7, 2024 • 23

Rethinking Data Selection at Scale: Random Selection is Almost All You Need

Paper • 2410.09335 • Published Oct 12, 2024 • 16
From Generalist to Specialist: Adapting Vision Language Models via Task-Specific Visual Instruction Tuning

Paper • 2410.06456 • Published Oct 9, 2024 • 37
Emergent properties with repeated examples

Paper • 2410.07041 • Published Oct 9, 2024 • 8
Personalized Visual Instruction Tuning

Paper • 2410.07113 • Published Oct 9, 2024 • 70

Training and finetune

AutoTrain: No-code training for state-of-the-art models

Paper • 2410.15735 • Published Oct 21, 2024 • 59

Pangea: A Fully Open Multilingual Multimodal LLM for 39 Languages

Paper • 2410.16153 • Published Oct 21, 2024 • 44
AutoTrain: No-code training for state-of-the-art models

Paper • 2410.15735 • Published Oct 21, 2024 • 59
The Curse of Multi-Modalities: Evaluating Hallucinations of Large Multimodal Models across Language, Visual, and Audio

Paper • 2410.12787 • Published Oct 16, 2024 • 31
LEOPARD : A Vision Language Model For Text-Rich Multi-Image Tasks

Paper • 2410.01744 • Published Oct 2, 2024 • 26

AutoTrain: No-code training for state-of-the-art models

Paper • 2410.15735 • Published Oct 21, 2024 • 59

Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

Paper • 1910.10683 • Published Oct 23, 2019 • 15
AutoTrain: No-code training for state-of-the-art models

Paper • 2410.15735 • Published Oct 21, 2024 • 59
LoRA Land: 310 Fine-tuned LLMs that Rival GPT-4, A Technical Report

Paper • 2405.00732 • Published Apr 29, 2024 • 121
LoRA: Low-Rank Adaptation of Large Language Models

Paper • 2106.09685 • Published Jun 17, 2021 • 54

AutoTrain: No-code training for state-of-the-art models

Paper • 2410.15735 • Published Oct 21, 2024 • 59

AutoTrain: No-code training for state-of-the-art models

Paper • 2410.15735 • Published Oct 21, 2024 • 59

papers to reading

FrugalNeRF: Fast Convergence for Few-shot Novel View Synthesis without Learned Priors

Paper • 2410.16271 • Published Oct 21, 2024 • 84
Baichuan Alignment Technical Report

Paper • 2410.14940 • Published Oct 19, 2024 • 51
SAM2Long: Enhancing SAM 2 for Long Video Segmentation with a Training-Free Memory Tree

Paper • 2410.16268 • Published Oct 21, 2024 • 69
AutoTrain: No-code training for state-of-the-art models

Paper • 2410.15735 • Published Oct 21, 2024 • 59

Interesting Papers

These papers are interesting (to me)

Revisit Large-Scale Image-Caption Data in Pre-training Multimodal Foundation Models

Paper • 2410.02740 • Published Oct 3, 2024 • 54
From Code to Correctness: Closing the Last Mile of Code Generation with Hierarchical Debugging

Paper • 2410.01215 • Published Oct 2, 2024 • 39
Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Multimodal Models

Paper • 2409.17146 • Published Sep 25, 2024 • 121
EuroLLM: Multilingual Language Models for Europe

Paper • 2409.16235 • Published Sep 24, 2024 • 29

EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters

Paper • 2402.04252 • Published Feb 6, 2024 • 29
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models

Paper • 2402.03749 • Published Feb 6, 2024 • 14
ScreenAI: A Vision-Language Model for UI and Infographics Understanding

Paper • 2402.04615 • Published Feb 7, 2024 • 44
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss

Paper • 2402.05008 • Published Feb 7, 2024 • 23

Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

Paper • 1910.10683 • Published Oct 23, 2019 • 15
AutoTrain: No-code training for state-of-the-art models

Paper • 2410.15735 • Published Oct 21, 2024 • 59
LoRA Land: 310 Fine-tuned LLMs that Rival GPT-4, A Technical Report

Paper • 2405.00732 • Published Apr 29, 2024 • 121
LoRA: Low-Rank Adaptation of Large Language Models

Paper • 2106.09685 • Published Jun 17, 2021 • 54

Rethinking Data Selection at Scale: Random Selection is Almost All You Need

Paper • 2410.09335 • Published Oct 12, 2024 • 16
From Generalist to Specialist: Adapting Vision Language Models via Task-Specific Visual Instruction Tuning

Paper • 2410.06456 • Published Oct 9, 2024 • 37
Emergent properties with repeated examples

Paper • 2410.07041 • Published Oct 9, 2024 • 8
Personalized Visual Instruction Tuning

Paper • 2410.07113 • Published Oct 9, 2024 • 70

AutoTrain: No-code training for state-of-the-art models

Paper • 2410.15735 • Published Oct 21, 2024 • 59

Training and finetune

AutoTrain: No-code training for state-of-the-art models

Paper • 2410.15735 • Published Oct 21, 2024 • 59

AutoTrain: No-code training for state-of-the-art models

Paper • 2410.15735 • Published Oct 21, 2024 • 59

Pangea: A Fully Open Multilingual Multimodal LLM for 39 Languages

Paper • 2410.16153 • Published Oct 21, 2024 • 44
AutoTrain: No-code training for state-of-the-art models

Paper • 2410.15735 • Published Oct 21, 2024 • 59
The Curse of Multi-Modalities: Evaluating Hallucinations of Large Multimodal Models across Language, Visual, and Audio

Paper • 2410.12787 • Published Oct 16, 2024 • 31
LEOPARD : A Vision Language Model For Text-Rich Multi-Image Tasks

Paper • 2410.01744 • Published Oct 2, 2024 • 26

papers to reading

FrugalNeRF: Fast Convergence for Few-shot Novel View Synthesis without Learned Priors

Paper • 2410.16271 • Published Oct 21, 2024 • 84
Baichuan Alignment Technical Report

Paper • 2410.14940 • Published Oct 19, 2024 • 51
SAM2Long: Enhancing SAM 2 for Long Video Segmentation with a Training-Free Memory Tree

Paper • 2410.16268 • Published Oct 21, 2024 • 69
AutoTrain: No-code training for state-of-the-art models

Paper • 2410.15735 • Published Oct 21, 2024 • 59

AutoTrain: No-code training for state-of-the-art models

Paper • 2410.15735 • Published Oct 21, 2024 • 59

Interesting Papers

These papers are interesting (to me)

Revisit Large-Scale Image-Caption Data in Pre-training Multimodal Foundation Models

Paper • 2410.02740 • Published Oct 3, 2024 • 54
From Code to Correctness: Closing the Last Mile of Code Generation with Hierarchical Debugging

Paper • 2410.01215 • Published Oct 2, 2024 • 39
Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Multimodal Models

Paper • 2409.17146 • Published Sep 25, 2024 • 121
EuroLLM: Multilingual Language Models for Europe

Paper • 2409.16235 • Published Sep 24, 2024 • 29

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