Computer Science · Artificial Intelligence
Deep-learning tools for predicting RNA splicing can rely on genomic clues unrelated to splicing and miss important effects of RNA structure, a study finds. These weaknesses were linked to systematic errors, especially when the tools evaluated sequences that differed from those used for training.
A study finds that shared data from split-learning phishing detectors can reveal private webpage information. A new attack using large language models outperformed conventional reconstruction attacks in experiments on real-world phishing datasets.
A preprint study found that the same hidden instruction could produce very different results in AI agents depending on whether it arrived as tool information or tool output, and what surrounded it. The findings have not been peer reviewed and may change.
A review finds that current safety certification rules do not map cleanly onto the behavior of large language models. It argues that safety-critical systems should certify the surrounding control system, keeping the language model in a role whose outputs are independently checked.
