A new framework combines the power of artificial intelligence with causal inference to better understand the factors driving legal decisions, going beyond simple pattern recognition.
Researchers have created a comprehensive evaluation framework to assess how well AI-powered robots can identify and avoid unsafe actions in typical household environments.
Researchers have developed a machine learning approach to identify and estimate the magnetic field strengths of white dwarf stars, revealing previously hidden objects.
Researchers have developed a new approach to robotic manipulation that allows robots to learn and execute intricate, multi-step tasks with greater efficiency and robustness.
New research explores how artificial intelligence can interpret the emotional nuances within the rich tradition of classical Persian poetry.
New research suggests the effectiveness of AI educational agents isn’t determined by the size of the underlying language model, but by the depth of their carefully crafted profiles.
A new framework leverages federated learning and Gaussian processes to enable teams of robots to efficiently explore and monitor environments.
A new framework enables multi-robot systems to accurately estimate their positions, even with limited communication and asynchronous sensor data.
![The Chem4DLLM model architecture processes three-dimensional molecular frames-each represented as [latex]\mathcal{X}\_{t}[/latex]-through a 4D equivariant graph encoder, transforming them into graph embeddings subsequently fused with special [latex]<graph>[/latex] tokens before being presented as a prefix sequence [latex]\mathbf{E}[/latex] to the Qwen3-8B language model for autoregressive output generation.](https://arxiv.org/html/2603.11924v1/x3.png)
A new approach combines artificial intelligence with 4D molecular trajectory data to unlock deeper understanding of chemical dynamics.
Researchers have developed a new framework that combines the power of large language models with a library of pre-defined skills to dramatically improve robotic disassembly success rates.