9 papers
The Heterogeneous Safety Impacts of Benign Multilingual Fine-Tuning
Will Hawkins, Kaivalya Rawal, Jonathan Rystrøm +8
Fine-tuning a large language model is a ubiquitous method for enhancing its capability on a specific downstream task. However, prior work has shown that this increase in capability…
AI-Mediated Communication Can Steer Collective Opinion
Stratis Tsirtsis, Kai Rawal, Chris Russell +2
Generative artificial intelligence (AI) is increasingly integrated into the online platforms where humans exchange opinions; large language models (LLMs) now polish users' posts on…
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…
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…
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…