The authors argue that current approaches to AI governance, which rely on jurisdiction-specific laws and policies, create a fragmented regulatory land...
Researchers argue that neural networks used for constraint satisfaction problems must be integrated with symbolic methods to ensure correctness. They ...
The machine learning community has a large presence in academic publishing, but reviewers often have negative experiences. Researchers propose using a...
Researchers used data from over 11,000 adolescents in a large study to compare different methods for predicting when young people might start using su...
Researchers have developed SKILL, a system that optimizes logic synthesis using a combination of large language models and reinforcement learning. SKI...
OGX is an open-source AI application server and Python library that allows developers to build agentic AI applications without changing their code. It...
Researchers have developed a unified framework called Euclid-Omni for tackling plane geometry problems. This system combines formal geometry with larg...
Researchers have developed an agentic framework using rules and Large Language Models (LLMs) to improve document layout analysis in plant science. The...
Researchers have found that errors in multi-agent language models can spread and become more difficult to detect as they pass through the pipeline. Th...
Researchers have conducted a survey to identify safe methods for Large Language Model (LLM) agents. They analyzed 38 studies and found that current ap...
Medical AI has made significant strides in diagnosis and prognosis, but its understanding of treatment is lacking. Instead of relying on human opinion...
Researchers at various institutions have created a benchmark to test the performance of large language models (LLMs) in temporal legal reasoning. They...