论文

• Layer by Layer: Uncovering Hidden Representations in Language Models
• s1: Simple test-time scaling
• SANA 1.5: Efficient Scaling of Training-Time and Inference-Time Compute in Linear Diffusion Transformer
• SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training
• Can We Generate Images with CoT? Let’s Verify and Reinforce Image Generation Step by Step
• Titans: Learning to Memorize at Test Time
• ReFocus: Visual Editing as a Chain of Thought for Structured Image Understanding
• DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
• Real-Time Video Generation with Pyramid Attention Broadcast
• Diffusion Models without Classifier-free Guidance
• CLIP Behaves like a Bag-of-Words Model Cross-modally but not Uni-modally
• I Think, Therefore I Diffuse: Enabling Multimodal In-Context Reasoning in Diffusion Models
• Deliberation in Latent Space via Differentiable Cache Augmentation
• Training Large Language Models to Reason in a Continuous Latent Space
• Hopping Too Late: Exploring the Limitations of Large Language Models on Multi-Hop Queries
• Distributional Reasoning in LLMs: Parallel Reasoning Processes in Multi-Hop Reasoning
• In-context Autoencoder for Context Compression in a Large Language Model
• DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models
• VoCo-LLaMA: Towards Vision Compression with Large Language Models
• Progressive Compositionality in Text-to-Image Generative Models
• GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation
• Fixed Point Diffusion Models
• Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach
• Visual Lexicon: Rich Image Features in Language Space
• DiffSensei: Bridging Multi-Modal LLMs and Diffusion Models for Customized Manga Generation
• Scaling Language-Free Visual Representation Learning
• Ming-Lite-Uni: Advancements in Unified Architecture for Natural Multimodal Interaction
• Harmonizing Visual Representations for Unified Multimodal Understanding and Generation
• T2I-R1: Reinforcing Image Generation with Collaborative Semantic-level and Token-level CoT
• Boosting Generative Image Modeling via Joint Image-Feature Synthesis
• Multi-modal Synthetic Data Training and Model Collapse: Insights from VLMs and Diffusion Models
• Mean Flows for One-step Generative Modeling
• Fractal Generative Models
• FlowTok: Flowing Seamlessly Across Text and Image Tokens
• DDT: Decoupled Diffusion Transformer
• Introducing Multiverse: The First AI Multiplayer World Model
• Lumina-Image 2.0: A Unified and Efficient Image Generative Framework
• Circuit Tracing: Revealing Computational Graphs in Language Models
• On the Biology of a Large Language Model
• PixelFlow: Pixel-Space Generative Models with Flow
• No Other Representation Component Is Needed: Diffusion Transformers Can Provide Representation Guidance by Themselves
• Visual Planning: Let’s Think Only with Images
• BLIP3-o: A Family of Fully Open Unified Multimodal Models—Architecture, Training and Dataset
• Bring Reason to Vision: Understanding Perception and Reasoning through Model Merging
• Emerging Properties in Unified Multimodal Pretraining
• Latent Flow Transformer
• Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?
• Efficient Pretraining Length Scaling
• Soft Thinking: Unlocking the Reasoning Potential of LLMs in Continuous Concept Space
• MMaDA: Multimodal Large Diffusion Language Models
• Harnessing the Universal Geometry of Embeddings
• Diffusion Meets Flow Matching: Two Sides of the Same Coin
• Elucidating the Design Space of Diffusion-Based Generative Models
• Noise Schedules Considered Harmful
• Unified Autoregressive Visual Generation and Understanding with Continuous Tokens
• Exploring the Latent Capacity of LLMs for One-Step Text Generation
• DataRater: Meta-Learned Dataset Curation
• A Fourier Space Perspective on Diffusion Models
• An Alchemist’s Notes on Deep Learning
• Spurious Rewards: Rethinking Training Signals in RLVR
• Envisioning Beyond the Pixels: Benchmarking Reasoning-Informed Visual Editing
• DetailFlow: 1D Coarse-to-Fine Autoregressive Image Generation via Next-Detail Prediction
• Hunyuan-Game: Industrial-grade Intelligent Game Creation Model
• Mathematical Theory of Deep Learning
• Atlas: Learning to Optimally Memorize the Context at Test Time
• Navigating the Latent Space Dynamics of Neural Models
• DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
• un2CLIP: Improving CLIP’s Visual Detail Capturing Ability via Inverting unCLIP
• Are Unified Vision-Language Models Necessary: Generalization Across Understanding and Generation
• VideoREPA: Learning Physics for Video Generation through Relational Alignment with Foundation Models
• Diffusion as Shader: 3D-aware Video Diffusion for Versatile Video Generation Control
• Stochastic Interpolants: A Unifying Framework for Flows and Diffusions
• Dual-Process Image Generation
• Continuous Thought Machines
• UniWorld: High-Resolution Semantic Encoders for Unified Visual Understanding and Generation
• How much do language models memorize?
• Object Concepts Emerge from Motion

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