Researchers have proposed a new method for analyzing the updates made to language models, specifically those used in medical specialization. The appro...
Researchers have proposed Conformalized Agentic Search (CAS), a framework for building reliable search agents. CAS addresses the reliability crisis in...
Researchers have developed an AI system that can author formal documents by reading a requester's forms and writing against them. They tested this sys...
Researchers have identified a problem with large language models (LLMs) called factual access failure. This occurs when LLMs can recognize the correct...
Researchers have developed a new method for evaluating the performance of mobile agents, such as robots or drones, that are guided by language. The ap...
Researchers have developed a new approach called dynamic context scheduling, which involves training AI models in a more realistic and varied environm...
Researchers have developed SPARC, a new method for motion forecasting that estimates uncertainty in a single pass. This approach combines Bayesian and...
Researchers have developed a method to combine brain activity data from EEG with environmental information to predict affective states. They used a da...
Researchers have proposed a method to improve the safety of large language models (LLMs) against multi-turn attacks. They introduce Multi-Turn Certifi...
Researchers have found that relying solely on prediction-based certification for trustworthy AI is not enough. They've demonstrated a separation theor...
Researchers have developed a new approach to identifying the cause-and-effect relationships in complex systems using observational data. They propose ...
A new framework called TRACE is designed to automatically enrich e-commerce product catalogs with missing or buried attributes. It uses a combination ...