8 citations · 17 across the 10 of their papers we have counts for
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cs.AI2026
Separable Expert Architecture: Toward Privacy-Preserving LLM Personalization via Composable Adapters and Deletable User Proxies
Chris Schneider, Philipp Schoenegger, Ben Bariach
Current model training approaches incorporate user information directly into shared weights, making individual data removal computationally infeasible without retraining. This pape…
cs.AI2026
Verifiable Semantics for Agent-to-Agent Communication
Philipp Schoenegger, Matt Carlson, Chris Schneider +1
Multiagent AI systems require consistent communication, but we lack methods to verify that agents share the same understanding of the terms used. Natural language is interpretable…