Trending Research
LTX-Video: Realtime Video Latent Diffusion
To address this, our VAE decoder is tasked with both latent-to-pixel conversion and the final denoising step, producing the clean result directly in pixel space.
OpenThinkIMG: Learning to Think with Images via Visual Tool Reinforcement Learning
We hope OpenThinkIMG can serve as a foundational framework for advancing dynamic, tool-augmented visual reasoning, helping the community develop AI agents that can genuinely "think with images".
Paper2Code: Automating Code Generation from Scientific Papers in Machine Learning
Despite the rapid growth of machine learning research, corresponding code implementations are often unavailable, making it slow and labor-intensive for researchers to reproduce results and build upon prior work.
Nexus-Gen: A Unified Model for Image Understanding, Generation, and Editing
To bridge this gap, we present Nexus-Gen, a unified model that synergizes the language reasoning capabilities of LLMs with the image synthesis power of diffusion models.
Unified Continuous Generative Models
LINs-Lab/UCGM
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We introduce a unified framework for training, sampling, and analyzing these models.
Ranked #1 on
Image Generation
on ImageNet 256x256
3D Scene Generation: A Survey
Recent advances in deep generative models (e. g., GANs, diffusion models) and 3D representations (e. g., NeRF, 3D Gaussians) have enabled the learning of real-world scene distributions, improving fidelity, diversity, and view consistency.
WebThinker: Empowering Large Reasoning Models with Deep Research Capability
Large reasoning models (LRMs), such as OpenAI-o1 and DeepSeek-R1, demonstrate impressive long-horizon reasoning capabilities.
Agent S2: A Compositional Generalist-Specialist Framework for Computer Use Agents
Computer use agents automate digital tasks by directly interacting with graphical user interfaces (GUIs) on computers and mobile devices, offering significant potential to enhance human productivity by completing an open-ended space of user queries.
Human-like Episodic Memory for Infinite Context LLMs
Large language models (LLMs) have shown remarkable capabilities, but still struggle with processing extensive contexts, limiting their ability to maintain coherence and accuracy over long sequences.
OpenHelix: A Short Survey, Empirical Analysis, and Open-Source Dual-System VLA Model for Robotic Manipulation
Dual-system VLA (Vision-Language-Action) architectures have become a hot topic in embodied intelligence research, but there is a lack of sufficient open-source work for further performance analysis and optimization.
