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Papers - Image - Clip

Demystifying CLIP Data

Paper • 2309.16671 • Published Sep 28, 2023 • 17
Model Stock: All we need is just a few fine-tuned models

Paper • 2403.19522 • Published Mar 28 • 9
Bigger is not Always Better: Scaling Properties of Latent Diffusion Models

Paper • 2404.01367 • Published Apr 1 • 19
On the Scalability of Diffusion-based Text-to-Image Generation

Paper • 2404.02883 • Published Apr 3 • 17

FaceChain-SuDe: Building Derived Class to Inherit Category Attributes for One-shot Subject-Driven Generation

Paper • 2403.06775 • Published Mar 11 • 3
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Paper • 2010.11929 • Published Oct 22, 2020 • 5
Data Incubation -- Synthesizing Missing Data for Handwriting Recognition

Paper • 2110.07040 • Published Oct 13, 2021 • 2
A Mixture of Expert Approach for Low-Cost Customization of Deep Neural Networks

Paper • 1811.00056 • Published Oct 31, 2018 • 2

Advanced and Recent Papers

Advanced and recent papers about deep learning. Please send your recommend paper to email: Tinghao.Zhang22@student.xjtlu.edu.cn

AutoCLIP: Auto-tuning Zero-Shot Classifiers for Vision-Language Models

Paper • 2309.16414 • Published Sep 28, 2023 • 19
Dynamic ASR Pathways: An Adaptive Masking Approach Towards Efficient Pruning of A Multilingual ASR Model

Paper • 2309.13018 • Published Sep 22, 2023 • 9
Robust Speech Recognition via Large-Scale Weak Supervision

Paper • 2212.04356 • Published Dec 6, 2022 • 11
Language models in molecular discovery

Paper • 2309.16235 • Published Sep 28, 2023 • 10

Kosmos-2.5: A Multimodal Literate Model

Paper • 2309.11419 • Published Sep 20, 2023 • 48
Mirasol3B: A Multimodal Autoregressive model for time-aligned and contextual modalities

Paper • 2311.05698 • Published Nov 9, 2023 • 6
Florence-2: Advancing a Unified Representation for a Variety of Vision Tasks

Paper • 2311.06242 • Published Nov 10, 2023 • 24
PolyMaX: General Dense Prediction with Mask Transformer

Paper • 2311.05770 • Published Nov 9, 2023 • 6

Everything about LLM

The Reversal Curse: LLMs trained on "A is B" fail to learn "B is A"

Paper • 2309.12288 • Published Sep 21, 2023 • 3
Are Emergent Abilities in Large Language Models just In-Context Learning?

Paper • 2309.01809 • Published Sep 4, 2023 • 3
When Less is More: Investigating Data Pruning for Pretraining LLMs at Scale

Paper • 2309.04564 • Published Sep 8, 2023 • 14
CulturaX: A Cleaned, Enormous, and Multilingual Dataset for Large Language Models in 167 Languages

Paper • 2309.09400 • Published Sep 17, 2023 • 77

PhotoVerse: Tuning-Free Image Customization with Text-to-Image Diffusion Models

Paper • 2309.05793 • Published Sep 11, 2023 • 50
InstaFlow: One Step is Enough for High-Quality Diffusion-Based Text-to-Image Generation

Paper • 2309.06380 • Published Sep 12, 2023 • 32
ImageBind-LLM: Multi-modality Instruction Tuning

Paper • 2309.03905 • Published Sep 7, 2023 • 15
DreamStyler: Paint by Style Inversion with Text-to-Image Diffusion Models

Paper • 2309.06933 • Published Sep 13, 2023 • 11

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AutoCLIP: Auto-tuning Zero-Shot Classifiers for Vision-Language Models

Paper • 2309.16414 • Published Sep 28, 2023 • 19
Demystifying CLIP Data

Paper • 2309.16671 • Published Sep 28, 2023 • 17

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