10 papers
Learning to Decide with AI Assistance under Human-Alignment
Nina Corvelo Benz, Eleni Straitouri, Manuel Gomez-Rodriguez
It is widely agreed that when AI models assist decision-makers in high-stakes domains by predicting an outcome of interest, they should communicate the confidence of their predicti…
Is Your LLM Overcharging You? Tokenization, Transparency, and Incentives
Ander Artola Velasco, Stratis Tsirtsis, Nastaran Okati +1
State-of-the-art large language models require specialized hardware and substantial energy to operate. As a consequence, cloud-based services that provide access to large language…
Optimizing Social Utility in Sequential Experiments
Ander Artola Velasco, Stratis Tsirtsis, Manuel Gomez-Rodriguez
Regulatory approval of products in high-stakes domains such as drug development requires statistical evidence of safety and efficacy through large-scale randomized controlled trial…
Test-Time Compute Games
Ander Artola Velasco, Dimitrios Rontogiannis, Stratis Tsirtsis +1
Test-time compute has emerged as a promising strategy to enhance the reasoning abilities of large language models (LLMs). However, this strategy has in turn increased how much user…
Evaluation of Large Language Models via Coupled Token Generation
Nina Corvelo Benz, Stratis Tsirtsis, Eleni Straitouri +4
State of the art large language models rely on randomization to respond to a prompt. As an immediate consequence, a model may respond differently to the same prompt if asked multip…
Auditing Pay-Per-Token in Large Language Models
Ander Artola Velasco, Stratis Tsirtsis, Manuel Gomez-Rodriguez
Millions of users rely on a market of cloud-based services to obtain access to state-of-the-art large language models. However, it has been very recently shown that the de facto pa…