Trending Research
Sa2VA: Marrying SAM2 with LLaVA for Dense Grounded Understanding of Images and Videos
This work presents Sa2VA, the first unified model for dense grounded understanding of both images and videos.
Hallo3: Highly Dynamic and Realistic Portrait Image Animation with Diffusion Transformer Networks
fudan-generative-vision/hallo3
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Existing methodologies for animating portrait images face significant challenges, particularly in handling non-frontal perspectives, rendering dynamic objects around the portrait, and generating immersive, realistic backgrounds.
Search-o1: Agentic Search-Enhanced Large Reasoning Models
To address this limitation, we introduce \textbf{Search-o1}, a framework that enhances LRMs with an agentic retrieval-augmented generation (RAG) mechanism and a Reason-in-Documents module for refining retrieved documents.
Ranked #1 on
Mathematical Reasoning
on MATH500
PPTAgent: Generating and Evaluating Presentations Beyond Text-to-Slides
Automatically generating presentations from documents is a challenging task that requires balancing content quality, visual design, and structural coherence.
LatentSync: Audio Conditioned Latent Diffusion Models for Lip Sync
Since we did not change the overall training framework of SyncNet, our experience can also be applied to other lip sync and audio-driven portrait animation methods that utilize SyncNet.
3DGS-to-PC: Convert a 3D Gaussian Splatting Scene into a Dense Point Cloud or Mesh
lewis-stuart-11/3dgs-to-pc
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The result is a point cloud that closely represents the shape encoded into the 3D Gaussian scene.
OASIS: Open Agent Social Interaction Simulations with One Million Agents
There has been a growing interest in enhancing rule-based agent-based models (ABMs) for social media platforms (i. e., X, Reddit) with more realistic large language model (LLM) agents, thereby allowing for a more nuanced study of complex systems.
TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second
automl/tabpfn
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We present TabPFN, a trained Transformer that can do supervised classification for small tabular datasets in less than a second, needs no hyperparameter tuning and is competitive with state-of-the-art classification methods.
Lifelong Learning of Large Language Model based Agents: A Roadmap
This survey is the first to systematically summarize the potential techniques for incorporating lifelong learning into LLM-based agents.
Cosmos World Foundation Model Platform for Physical AI
nvidia/cosmos
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We position a world foundation model as a general-purpose world model that can be fine-tuned into customized world models for downstream applications.
