Researchers have developed a method for language models to solve constraint problems more reliably. They do this by translating the problem into a for...
Researchers from Qian Yin and colleagues propose a task-driven three-layer distributed scheduling method for emergency Earth observation in large low-...
Researchers have developed a new framework called CEDAR-GRPO to improve the abductive reasoning capabilities of large language models (LLMs). Abductiv...
A new study explores the concept of an AI advice channel that can influence human behavior without direct control. The research suggests that even if ...
Researchers argue that current large language models (LLMs) used in clinical AI lack a persistent, governed representation of patient information. The...
Researchers evaluated how well large language models (LLMs) can ask questions and gather information to answer complex queries. They created a control...
Researchers have proposed a new method for training language agents to balance multiple objectives. The approach, called MINT, involves ranking candid...
Researchers have developed a new system called Trident for answering questions about long documents that contain text, tables, charts, and figures. Th...
Researchers have developed an offline reinforcement learning method to automatically generate high-quality chess puzzles. They used a dataset of 1.5 b...
Researchers have proposed an always-on intelligence system called Jarvis that acts as a mediator between humans and agents working in the background. ...
Researchers propose a framework for AI systems to serve as personalized co-scientists by incorporating individual researcher representations into ever...
Researchers have audited the evidence supporting quantitative forecasts of frontier artificial intelligence. They found that many connections between ...