Understanding long videos, such as 24-hour CCTV footage or full-length films, is a major challenge in video processing. Large Language Models (LLMs) have shown great potential in handling multimodal ...

Reconstructing unmeasured causal drivers of complex time series from observed response data represents a fundamental challenge across diverse scientific domains. Latent variables, including genetic ...

Multimodal AI integrates diverse data formats, such as text and images, to create systems capable of accurately understanding and generating content. By bridging textual... The advancements in large ...

The advancements in large language models (LLMs) have significantly enhanced natural language processing (NLP), enabling capabilities like contextual understanding, code generation, and reasoning.

Reinforcement learning (RL) focuses on enabling agents to learn optimal behaviors through reward-based training mechanisms. These methods have empowered systems to tackle increasingly complex tasks, ...

Open Source LLM development is going through great change through fully reproducing and open-sourcing DeepSeek-R1, including training data, scripts, etc. Hosted on Hugging Face’s platform, this ...

Mixture-of-Experts (MoE) models utilize a router to allocate tokens to specific expert modules, activating only a subset of parameters, often leading to superior efficiency and performance compared to ...

Reinforcement learning (RL) focuses on enabling agents to learn optimal behaviors through reward-based training mechanisms. These methods have empowered systems to tackle increasingly complex tasks, ...

Advancements in multimodal intelligence depend on processing and understanding images and videos. Images can reveal static scenes by providing information regarding details such as objects, text, and ...

AI has entered an era of the rise of competitive and groundbreaking large language models and multimodal models. The development has two sides, one with open source and the other being propriety ...

Novel view synthesis has witnessed significant advancements recently, with Neural Radiance Fields (NeRF) pioneering 3D representation techniques through neural rendering. While NeRF introduced ...

Reinforcement learning (RL) focuses on enabling agents to learn optimal behaviors through reward-based training mechanisms. These methods have empowered systems to tackle increasingly complex tasks, ...