4 papers · 1 filter
Explaining Too Much? Understanding How Large Language Model Reasoning Traces Influence Performance and Metacognition
Daniela Fernandes, Daniel Buschek, Lev Tankelevitch +2
Large Language Model interfaces are increasingly verbose, exposing intermediate reasoning traces alongside final answers. Traces are framed as transparency mechanisms, yet it is un…
The AI Memory Gap: Users Misremember What They Created With AI or Without
Tim Zindulka, Sven Goller, Daniela Fernandes +2
As large language models (LLMs) become embedded in interactive text generation, disclosure of AI as a source depends on people remembering which ideas or texts came from themselves…
Performance and Metacognition Disconnect when Reasoning in Human-AI Interaction
Daniela Fernandes, Steeven Villa, Salla Nicholls +6
Optimizing human-AI interaction requires users to reflect on their own performance critically. Our paper examines whether people using AI to complete tasks can accurately monitor h…
Questionnaires for Everyone: Streamlining Cross-Cultural Questionnaire Adaptation with GPT-Based Translation Quality Evaluation
Otso Haavisto, Robin Welsch
Adapting questionnaires to new languages is a resource-intensive process often requiring the hiring of multiple independent translators, which limits the ability of researchers to…