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Collections including paper arxiv:2407.02687

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RLHF Workflow: From Reward Modeling to Online RLHF

Paper • 2405.07863 • Published May 13 • 62
Chameleon: Mixed-Modal Early-Fusion Foundation Models

Paper • 2405.09818 • Published May 16 • 119
Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models

Paper • 2405.15574 • Published May 24 • 52
An Introduction to Vision-Language Modeling

Paper • 2405.17247 • Published May 27 • 78

No Training, No Problem: Rethinking Classifier-Free Guidance for Diffusion Models

Paper • 2407.02687 • Published 25 days ago • 20
Inference Performance Optimization for Large Language Models on CPUs

Paper • 2407.07304 • Published 18 days ago • 48

Controlling Space and Time with Diffusion Models

Paper • 2407.07860 • Published 17 days ago • 15
DisCo-Diff: Enhancing Continuous Diffusion Models with Discrete Latents

Paper • 2407.03300 • Published 24 days ago • 10
Diffusion Forcing: Next-token Prediction Meets Full-Sequence Diffusion

Paper • 2407.01392 • Published 26 days ago • 39
No Training, No Problem: Rethinking Classifier-Free Guidance for Diffusion Models

Paper • 2407.02687 • Published 25 days ago • 20

PaperWaitingRead

A False Sense of Safety: Unsafe Information Leakage in 'Safe' AI Responses

Paper • 2407.02551 • Published 25 days ago • 7
DisCo-Diff: Enhancing Continuous Diffusion Models with Discrete Latents

Paper • 2407.03300 • Published 24 days ago • 10
TokenPacker: Efficient Visual Projector for Multimodal LLM

Paper • 2407.02392 • Published 25 days ago • 20
No Training, No Problem: Rethinking Classifier-Free Guidance for Diffusion Models

Paper • 2407.02687 • Published 25 days ago • 20

Papers - Image - Classifier-Free Guidance (CFG)

Guidance - "The intended effect is to decrease the diversity of the samples while increasing the quality of each individual sample."

Classifier-Free Diffusion Guidance

Paper • 2207.12598 • Published Jul 26, 2022 • 2
Adding Conditional Control to Text-to-Image Diffusion Models

Paper • 2302.05543 • Published Feb 10, 2023 • 32
Applying Guidance in a Limited Interval Improves Sample and Distribution Quality in Diffusion Models

Paper • 2404.07724 • Published Apr 11 • 10
Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation

Paper • 2406.06525 • Published Jun 10 • 62

Image-Gen Theoretical

Guiding a Diffusion Model with a Bad Version of Itself

Paper • 2406.02507 • Published Jun 4 • 15
Step-aware Preference Optimization: Aligning Preference with Denoising Performance at Each Step

Paper • 2406.04314 • Published Jun 6 • 26
An Image is Worth 32 Tokens for Reconstruction and Generation

Paper • 2406.07550 • Published Jun 11 • 54
Commonsense-T2I Challenge: Can Text-to-Image Generation Models Understand Commonsense?

Paper • 2406.07546 • Published Jun 11 • 8

CatLIP: CLIP-level Visual Recognition Accuracy with 2.7x Faster Pre-training on Web-scale Image-Text Data

Paper • 2404.15653 • Published Apr 24 • 25
MoDE: CLIP Data Experts via Clustering

Paper • 2404.16030 • Published Apr 24 • 11
MoRA: High-Rank Updating for Parameter-Efficient Fine-Tuning

Paper • 2405.12130 • Published May 20 • 44
Reducing Transformer Key-Value Cache Size with Cross-Layer Attention

Paper • 2405.12981 • Published May 21 • 26

AniClipart: Clipart Animation with Text-to-Video Priors

Paper • 2404.12347 • Published Apr 18 • 11
MoA: Mixture-of-Attention for Subject-Context Disentanglement in Personalized Image Generation

Paper • 2404.11565 • Published Apr 17 • 12
Dynamic Typography: Bringing Words to Life

Paper • 2404.11614 • Published Apr 17 • 40
No Training, No Problem: Rethinking Classifier-Free Guidance for Diffusion Models

Paper • 2407.02687 • Published 25 days ago • 20

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 • 6
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

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