Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation
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2406.06525
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Published
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62
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Husky: A Unified, Open-Source Language Agent for Multi-Step Reasoning
Paper • 2406.06469 • Published • 22 -
Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models
Paper • 2406.04271 • Published • 27 -
Block Transformer: Global-to-Local Language Modeling for Fast Inference
Paper • 2406.02657 • Published • 36 -
Mobile-Agent-v2: Mobile Device Operation Assistant with Effective Navigation via Multi-Agent Collaboration
Paper • 2406.01014 • Published • 29 -
PosterLLaVa: Constructing a Unified Multi-modal Layout Generator with LLM
Paper • 2406.02884 • Published • 13 -
Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms
Paper • 2406.02900 • Published • 10 -
RoboCasa: Large-Scale Simulation of Everyday Tasks for Generalist Robots
Paper • 2406.02523 • Published • 8 -
Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality
Paper • 2405.21060 • Published • 61 -
Jina CLIP: Your CLIP Model Is Also Your Text Retriever
Paper • 2405.20204 • Published • 28 -
Xwin-LM: Strong and Scalable Alignment Practice for LLMs
Paper • 2405.20335 • Published • 17 -
Mixture-of-Agents Enhances Large Language Model Capabilities
Paper • 2406.04692 • Published • 50 -
MAP-Neo: Highly Capable and Transparent Bilingual Large Language Model Series
Paper • 2405.19327 • Published • 43 -
2BP: 2-Stage Backpropagation
Paper • 2405.18047 • Published • 21 -
Phased Consistency Model
Paper • 2405.18407 • Published • 44 -
Yuan 2.0-M32: Mixture of Experts with Attention Router
Paper • 2405.17976 • Published • 18 -
An Introduction to Vision-Language Modeling
Paper • 2405.17247 • Published • 78 -
Transformers Can Do Arithmetic with the Right Embeddings
Paper • 2405.17399 • Published • 50 -
Human4DiT: Free-view Human Video Generation with 4D Diffusion Transformer
Paper • 2405.17405 • Published • 14 -
Trans-LoRA: towards data-free Transferable Parameter Efficient Finetuning
Paper • 2405.17258 • Published • 12 -
LoGAH: Predicting 774-Million-Parameter Transformers using Graph HyperNetworks with 1/100 Parameters
Paper • 2405.16287 • Published • 10 -
Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models
Paper • 2405.15574 • Published • 52 -
ConvLLaVA: Hierarchical Backbones as Visual Encoder for Large Multimodal Models
Paper • 2405.15738 • Published • 43 -
Stacking Your Transformers: A Closer Look at Model Growth for Efficient LLM Pre-Training
Paper • 2405.15319 • Published • 23 -
AutoCoder: Enhancing Code Large Language Model with AIEV-Instruct
Paper • 2405.14906 • Published • 21 -
Automatic Data Curation for Self-Supervised Learning: A Clustering-Based Approach
Paper • 2405.15613 • Published • 12 -
HDR-GS: Efficient High Dynamic Range Novel View Synthesis at 1000x Speed via Gaussian Splatting
Paper • 2405.15125 • Published • 5 -
Not All Language Model Features Are Linear
Paper • 2405.14860 • Published • 39 -
DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data
Paper • 2405.14333 • Published • 29 -
Dense Connector for MLLMs
Paper • 2405.13800 • Published • 20 -
Your Transformer is Secretly Linear
Paper • 2405.12250 • Published • 147 -
Reducing Transformer Key-Value Cache Size with Cross-Layer Attention
Paper • 2405.12981 • Published • 26 -
Face Adapter for Pre-Trained Diffusion Models with Fine-Grained ID and Attribute Control
Paper • 2405.12970 • Published • 22 -
Diffusion for World Modeling: Visual Details Matter in Atari
Paper • 2405.12399 • Published • 25 -
MoRA: High-Rank Updating for Parameter-Efficient Fine-Tuning
Paper • 2405.12130 • Published • 44 -
OpenRLHF: An Easy-to-use, Scalable and High-performance RLHF Framework
Paper • 2405.11143 • Published • 33 -
Imp: Highly Capable Large Multimodal Models for Mobile Devices
Paper • 2405.12107 • Published • 23 -
LoRA Learns Less and Forgets Less
Paper • 2405.09673 • Published • 81 -
Many-Shot In-Context Learning in Multimodal Foundation Models
Paper • 2405.09798 • Published • 26 -
What matters when building vision-language models?
Paper • 2405.02246 • Published • 93