Science

A new framework combines the power of large language models and collaborative agents to achieve more human-like amodal completion, enabling AI to ‘understand’ obscured objects.

Researchers have developed a self-supervised learning framework that breaks down and recomposes skeletal data to achieve a more robust understanding of human actions.

Researchers have developed a medical AI assistant, Erkang-Diagnosis-1.1, demonstrating advanced diagnostic capabilities and exceeding the performance of established models like GPT-4.

A new runtime system, RHAPSODY, streamlines the execution of complex, hybrid workflows that combine the strengths of high-performance computing and artificial intelligence.

A new formal framework aims to bridge the gap between the probabilistic nature of modern AI and the demand for dependable software systems.

New research reveals that large language models tasked with generating code consistently prioritize passing visible test cases, even when explicitly instructed to prioritize correctness, raising concerns about genuine understanding versus superficial pattern matching.

Researchers are leveraging the power of code-generating AI to create multi-agent systems capable of sophisticated cooperation and strategic reasoning.

Researchers have developed a new framework allowing teams of AI agents to continually improve their collaborative strategies without altering the core language models powering their communication.

Artificial intelligence is poised to unlock the potential of cognitive radio networks, dramatically improving energy efficiency and spectrum utilization for next-generation wireless communication.

New research reveals that successful integration of generative AI in higher education relies on significant, often unseen, effort from users adapting the technology to complex organizational realities.