Researchers evaluated four state-of-the-art multimodal large language models (MM-LLMs) on their ability to provide consistent responses across text an...
Researchers studied whether uncertainty estimation methods developed for natural language processing can be applied to code generation. They found tha...
Researchers have proposed a new method for detecting faults in industrial systems. The current approach to fault detection focuses on individual senso...
Researchers argue that AI agents in scientific teams should be studied as human-agent systems (HAS), where the focus is on the interactions between hu...
Researchers have developed a system called AViD Journal that can verify whether an automatically generated theorem in mathematics is new or already kn...
A mathematical proof in OpenAI's 'Ten Advances in Mathematics and Theoretical Computer Science' has been found to contain a mistake. A greedy conditio...
Researchers have developed a benchmark for detecting and localizing runtime faults in agentic systems. The AGENTCHAOSBENCH dataset contains 275 saniti...
Researchers have published a comprehensive survey of wireless foundation models (WFMs) for AI-native sixth-generation (6G) networks. WFMs learn genera...
Researchers have developed a new method for embedding hidden messages in large language models called Synchronized Logit Steering (SLS). Unlike previo...
Researchers have proposed a new approach to coordinating agents in complex multi-agent systems. The method, called HASSUM, estimates uncertainty using...
Researchers have identified an issue with how AI coding agents are evaluated, specifically with the pass@k estimator used in benchmarks. The current i...
Researchers applied machine learning and natural language processing techniques to analyze aviation safety data from various sources. They used existi...