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cs.AI2026

Tailored to you: longitudinal effects of personalising language models

Canfer Akbulut, Justine Breuch, Arianna Manzini +6

Interest in developing personalised language models is rapidly growing. While personalisation is often viewed as a mechanism to better serve diverse user needs, the effects of sust…

cs.AI2026

Long-term Measurements: Towards a Longitudinal Understanding of Human-AI Interactions

Nicole Mitchell, Dhruv Agarwal, Maty Bohacek +2

Language models have taken on the role of a very new type of technology, by virtue of their "human-ness" and rapid integration into users' daily lives. This combination of features…

cs.CL2026

Pluralis v0.1: Towards a Multicultural, Multimodal, Multilingual Benchmark for AI Risk and Reliability

Alicia Parrish, Rajat Shinde, Sanket Badhe +57

Current AI safety evaluation and benchmarking frameworks predominantly rely on Western-centric culture-agnostic defaults that mask critical regional laws, socio-linguistic nuances,…

cs.AI2026

Detecting and Controlling Sycophancy with Cascading Linear Features

Maty Bohacek, Rishub Jain, Nicholas Dufour +3

Interpreting and controlling model behaviors through activation steering methods requires many pairs of contrastive samples that clearly exhibit desired or undesired behavior. Thes…

cs.AI2026

Positive Alignment: Artificial Intelligence for Human Flourishing

Ruben Laukkonen, Seb Krier, Chloé Bakalar +13

Existing alignment research is dominated by concerns about safety and preventing harm: safeguards, controllability, and compliance. This paradigm of alignment parallels early psych…