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cs.AI2026
Scaling Participation in Modular AI Systems
Shangbin Feng, Yike Wang, Weijia Shi +3
Humanity is a mosaic of multifaceted talents and needs, and any truly intelligent AI must reflect that richness. Yet the LLMs used by all are built by the few -- a centralized mark…
cs.AI2024
Can LLMs Keep a Secret? Testing Privacy Implications of Language Models via Contextual Integrity Theory
Niloofar Mireshghallah, Hyunwoo Kim, Xuhui Zhou +4
The interactive use of large language models (LLMs) in AI assistants (at work, home, etc.) introduces a new set of inference-time privacy risks: LLMs are fed different types of inf…