Researchers have developed a web-based tool called Graphectory Viewer for analyzing software-agent trajectories. The tool transforms raw data into gra...
Researchers have developed an agent-centered architecture for general robot learning called Teach-and-Grow Learning (TGL). This approach allows robots...
Researchers have developed a framework called PACE to ensure the safety of AI agents in decentralized finance. PACE introduces typed transaction inten...
Researchers have developed a self-supervised framework called Delta2Gamma for detecting Alzheimer's disease using electroencephalography (EEG) recordi...
A new safety gate for multimodal large language models (MLLMs) called COMIC has been proposed to address a structural weakness in current defenses. Cu...
Researchers have developed a framework to convert structural framing plans into editable finite-element model drafts. The system uses an agentic visio...
Researchers propose using a $q$Gaussian distribution derived from Tsallis entropy maximization as an alternative to Gaussian models in statistical spa...
Researchers have developed an adaptive surrogate modeling method for problems with high-dimensional spatio-temporal outputs. This approach uses dimens...
Researchers have developed a new framework called Co-RL that enables unsupervised reasoning in reinforcement learning. Unlike traditional self-rewardi...
Researchers have developed a new method for reconstructing CT scans from just two X-ray images. The approach, called LiftXR, first generates a 3D layo...
Researchers have developed a nonadaptive learning method for robust nonlinear output regulation in control systems. This approach combines an input-dr...
Researchers analyzed the effectiveness of 'curriculum learning' in large language models by examining how different schedules for training data affect...