7 papers
Dr.LLM: Dynamic Layer Routing in LLMs
Ahmed Heakl, Martin Gubri, Salman Khan +2
Large Language Models (LLMs) process every token through all layers of a transformer stack, causing wasted computation on simple queries and insufficient flexibility for harder one…
DISCO: Diversifying Sample Condensation for Efficient Model Evaluation
Alexander Rubinstein, Benjamin Raible, Martin Gubri +1
Evaluating modern machine learning models has become prohibitively expensive. Benchmarks such as LMMs-Eval and HELM demand thousands of GPU hours per model. Costly evaluation reduc…
C-SEO Bench: Does Conversational SEO Work?
Haritz Puerto, Martin Gubri, Tommaso Green +2
Large Language Models (LLMs) are transforming search engines into Conversational Search Engines (CSE). Consequently, Search Engine Optimization (SEO) is being shifted into Conversa…
Leaky Thoughts: Large Reasoning Models Are Not Private Thinkers
Tommaso Green, Martin Gubri, Haritz Puerto +2
We study privacy leakage in the reasoning traces of large reasoning models used as personal agents. Unlike final outputs, reasoning traces are often assumed to be internal and safe…
Social Science Is Necessary for Operationalizing Socially Responsible Foundation Models
Adam Davies, Elisa Nguyen, Michael Simeone +2
With the rise of foundation models, there is growing concern about their potential social impacts. Social science has a long history of studying the social impacts of transformativ…
Testing Uniform Random Samplers: Methods, Datasets and Protocols
Olivier Zeyen, Maxime Cordy, Martin Gubri +2
Boolean formulae compactly encode huge, constrained search spaces. Thus, variability-intensive systems are often encoded with Boolean formulae. The search space of a variability-in…