2 citations · 2 across the 11 of their papers we have counts for
6 papers · 1 filter
Narrowing Action Choices with AI Improves Human Sequential Decisions
Eleni Straitouri, Stratis Tsirtsis, Ander Artola Velasco +1
Recent work has shown that, in classification tasks, it is possible to design decision support systems that do not require human experts to understand when to cede agency to a clas…
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…
Towards Human-AI Complementarity in Matching Tasks
Adrian Arnaiz-Rodriguez, Nina Corvelo Benz, Suhas Thejaswi +2
Data-driven algorithmic matching systems promise to help human decision makers make better matching decisions in a wide variety of high-stakes application domains, such as healthca…
Tokenization Multiplicity Leads to Arbitrary Price Variation in LLM-as-a-service
Ivi Chatzi, Nina Corvelo Benz, Stratis Tsirtsis +1
Providers of LLM-as-a-service have predominantly adopted a simple pricing model: users pay a fixed price per token. Consequently, one may think that the price two different users w…
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…
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…