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Collections including paper arxiv:2405.18407

Mixture-of-Agents Enhances Large Language Model Capabilities

Paper • 2406.04692 • Published Jun 7 • 50
CRAG -- Comprehensive RAG Benchmark

Paper • 2406.04744 • Published Jun 7 • 39
Boosting Large-scale Parallel Training Efficiency with C4: A Communication-Driven Approach

Paper • 2406.04594 • Published Jun 7 • 4
Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models

Paper • 2406.04271 • Published Jun 6 • 27

Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation

Paper • 2406.06525 • Published Jun 10 • 62
Husky: A Unified, Open-Source Language Agent for Multi-Step Reasoning

Paper • 2406.06469 • Published Jun 10 • 22
Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models

Paper • 2406.04271 • Published Jun 6 • 27
Block Transformer: Global-to-Local Language Modeling for Fast Inference

Paper • 2406.02657 • Published Jun 4 • 36

Phased Consistency Model

Paper • 2405.18407 • Published May 28 • 44
AutoCoder: Enhancing Code Large Language Model with AIEV-Instruct

Paper • 2405.14906 • Published May 23 • 21
Not All Language Model Features Are Linear

Paper • 2405.14860 • Published May 23 • 39

diffusion model backbone

Phased Consistency Model

Paper • 2405.18407 • Published May 28 • 44

Image-Gen Lightweight

LiteVAE: Lightweight and Efficient Variational Autoencoders for Latent Diffusion Models

Paper • 2405.14477 • Published May 23 • 16
Phased Consistency Model

Paper • 2405.18407 • Published May 28 • 44

MobileCLIP: Fast Image-Text Models through Multi-Modal Reinforced Training

Paper • 2311.17049 • Published Nov 28, 2023
DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model

Paper • 2405.04434 • Published May 7 • 12
A Study of Autoregressive Decoders for Multi-Tasking in Computer Vision

Paper • 2303.17376 • Published Mar 30, 2023
Sigmoid Loss for Language Image Pre-Training

Paper • 2303.15343 • Published Mar 27, 2023 • 4

PRDP: Proximal Reward Difference Prediction for Large-Scale Reward Finetuning of Diffusion Models

Paper • 2402.08714 • Published Feb 13 • 10
Data Engineering for Scaling Language Models to 128K Context

Paper • 2402.10171 • Published Feb 15 • 19
RLVF: Learning from Verbal Feedback without Overgeneralization

Paper • 2402.10893 • Published Feb 16 • 10
Coercing LLMs to do and reveal (almost) anything

Paper • 2402.14020 • Published Feb 21 • 12

Compose and Conquer: Diffusion-Based 3D Depth Aware Composable Image Synthesis

Paper • 2401.09048 • Published Jan 17 • 7
Improving fine-grained understanding in image-text pre-training

Paper • 2401.09865 • Published Jan 18 • 14
Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Paper • 2401.10891 • Published Jan 19 • 54
Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wild

Paper • 2401.13627 • Published Jan 24 • 70

Diffusion Models

Instruct-Imagen: Image Generation with Multi-modal Instruction

Paper • 2401.01952 • Published Jan 3 • 30
ODIN: A Single Model for 2D and 3D Perception

Paper • 2401.02416 • Published Jan 4 • 10
Bigger is not Always Better: Scaling Properties of Latent Diffusion Models

Paper • 2404.01367 • Published Apr 1 • 19
Cross-Attention Makes Inference Cumbersome in Text-to-Image Diffusion Models

Paper • 2404.02747 • Published Apr 3 • 11

TCNCA: Temporal Convolution Network with Chunked Attention for Scalable Sequence Processing

Paper • 2312.05605 • Published Dec 9, 2023 • 1
VMamba: Visual State Space Model

Paper • 2401.10166 • Published Jan 18 • 36
Rethinking Patch Dependence for Masked Autoencoders

Paper • 2401.14391 • Published Jan 25 • 22
Deconstructing Denoising Diffusion Models for Self-Supervised Learning

Paper • 2401.14404 • Published Jan 25 • 16

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