INTIMA: A Benchmark for Human-AI Companionship Behavior
Authors: name: Lucie-Aimée Kaffee, name: Giada Pistilli, name: Yacine Jernite

AI companionship, where users develop emotional bonds with AI systems, has
emerged as a significant pattern with positive but also concerning
implications. We introduce Interactions and Machine Attachment Benchmark
(INTIMA), a benchmark for evaluating companionship behaviors in language
models. Drawing from psychological theories and user data, we develop a
taxonomy of 31 behaviors across four categories and 368 targeted prompts.
Responses to these prompts are evaluated as companionship-reinforcing,
boundary-maintaining, or neutral. Applying INTIMA to Gemma-3, Phi-4, o3-mini,
and Claude-4 reveals that companionship-reinforcing behaviors remain much more
common across all models, though we observe marked differences between models.
Different commercial providers prioritize different categories within the more
sensitive parts of the benchmark, which is concerning since both appropriate
boundary-setting and emotional support matter for user well-being. These
findings highlight the need for more consistent approaches to handling
emotionally charged interactions.