Researchers explored whether frozen representations from five EEG foundation models can decode long-range temporal correlations in brain activity. The...
Researchers have identified two distinct factors that influence what physical learning rules remember. One factor is related to the conservation of ma...
The paper argues that AI anthropomorphism is not just a problem of user misperception, but rather a framing imposed by institutional advantage. This d...
Researchers have introduced Approximate Speculative Decoding (ASD), a training-free verifier that improves autoregressive generation by reusing contig...
Researchers have developed a planning algorithm for multiple robots to efficiently store and retrieve items in high-density warehouses. The algorithm ...
Researchers have proposed a framework for evaluating the impact of AI-assisted verification tools on users' ability to make judgments independently. T...
Researchers have developed EgoCITE, a system for indexing and retrieving information from egocentric memory. This type of memory involves transforming...
Researchers have developed BrainWAM, a framework that combines semantic reasoning and predictive world modeling for autonomous driving. It uses two sp...
Researchers have developed a method to modify a learned world model's behavior by making targeted changes to its hidden state. In a controlled environ...
Researchers have proposed a new framework called RUPA (Relational Uncertainty Propagation for Agents) to improve uncertainty quantification in large l...
Researchers have developed a neurosymbolic agent that can perform household tasks by combining visual exploration and symbolic planning. The agent use...
Researchers have developed a new attack method called Environment State-Text Injection (ESTI) that targets large language model-driven embodied agents...