5 papers
Improving Explanations: Applying the Feature Understandability Scale for Cost-Sensitive Feature Selection
Nicola Rossberg, Bennett Kleinberg, Barry O'Sullivan +2
With the growing pervasiveness of artificial intelligence, the ability to explain the inferences made by machine learning models has become increasingly important. Numerous techniq…
Human attribution of empathic behaviour to AI systems
Jonas Festor, Ivo Snels, Bennett Kleinberg
Artificial intelligence systems increasingly generate text intended to provide social and emotional support. Understanding how users perceive empathic qualities in such content is…
When lies are mostly truthful: automated verbal deception detection for embedded lies
Riccardo Loconte, Bennett Kleinberg
Background: Verbal deception detection research relies on narratives and commonly assumes statements as truthful or deceptive. A more realistic perspective acknowledges that the ve…
Linguistic traces of stochastic empathy in language models
Bennett Kleinberg, Jari Zegers, Jonas Festor +4
Differentiating generated and human-written content is increasingly difficult. We examine how an incentive to convey humanness and task characteristics shape this human vs AI race…
Cognitive phantoms in LLMs through the lens of latent variables
Sanne Peereboom, Inga Schwabe, Bennett Kleinberg
Large language models (LLMs) increasingly reach real-world applications, necessitating a better understanding of their behaviour. Their size and complexity complicate traditional a…