Trending Research
Step-Video-T2V Technical Report: The Practice, Challenges, and Future of Video Foundation Model
We present Step-Video-T2V, a state-of-the-art text-to-video pre-trained model with 30B parameters and the ability to generate videos up to 204 frames in length.
OmniParser for Pure Vision Based GUI Agent
The recent success of large vision language models shows great potential in driving the agent system operating on user interfaces.
Ranked #10 on
Natural Language Visual Grounding
on ScreenSpot
PIKE-RAG: sPecIalized KnowledgE and Rationale Augmented Generation
Despite notable advancements in Retrieval-Augmented Generation (RAG) systems that expand large language model (LLM) capabilities through external retrieval, these systems often struggle to meet the complex and diverse needs of real-world industrial applications.
CodeI/O: Condensing Reasoning Patterns via Code Input-Output Prediction
Reasoning is a fundamental capability of Large Language Models.
Data Formulator 2: Iteratively Creating Rich Visualizations with AI
To create rich visualizations, data analysts often need to iterate back and forth among data processing and chart specification to achieve their goals.
Magic 1-For-1: Generating One Minute Video Clips within One Minute
da-group-pku/magic-1-for-1
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The key idea is simple: factorize the text-to-video generation task into two separate easier tasks for diffusion step distillation, namely text-to-image generation and image-to-video generation.
Light-A-Video: Training-free Video Relighting via Progressive Light Fusion
Second, leveraging the physical principle of light transport independence, we apply linear blending between the source video's appearance and the relighted appearance, using a Progressive Light Fusion (PLF) strategy to ensure smooth temporal transitions in illumination.
KET-RAG: A Cost-Efficient Multi-Granular Indexing Framework for Graph-RAG
To ensure a good result accuracy while reducing the indexing cost, we propose KET-RAG, a multi-granular indexing framework.
Flaming-hot Initiation with Regular Execution Sampling for Large Language Models
volcengine/verl
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Since the release of ChatGPT, large language models (LLMs) have demonstrated remarkable capabilities across various domains.
Diffusion Models without Classifier-free Guidance
This paper presents Model-guidance (MG), a novel objective for training diffusion model that addresses and removes of the commonly used Classifier-free guidance (CFG).
Ranked #1 on
Image Generation
on ImageNet 256x256
