65 citations · 99 across the 11 of their papers we have counts for
Showing cs.CLShow all
2 papers · 1 filter
cs.CL2026
Failure of contextual invariance in large language models
Sagar Kumar, Ariel Flint, Luca Maria Aiello +1
Standard evaluation practices assume that large language model (LLM) outputs are stable when prompts are embedded in contextually equivalent discourses. Here, we test this assumpti…
cs.CL2025
Reply to "Emergent LLM behaviors are observationally equivalent to data leakage"
Ariel Flint Ashery, Luca Maria Aiello, Andrea Baronchelli
A potential concern when simulating populations of large language models (LLMs) is data contamination, i.e. the possibility that training data may shape outcomes in unintended ways…