Survey of 112 agentic AI for social good papers reveals moral-geographic asymmetry with 73% lacking geographic context (lowest for SDG 16) and only 25% reporting deployments.
Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology , year=
2 Pith papers cite this work. Polarity classification is still indexing.
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RealUserSim grounds LLM simulators in 7,275 executable profiles from real conversations, raising behavioral match rates from 24.2% to 45.3% and revealing agent failures hidden by cooperative simulators.
citing papers explorer
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Whose Good, Whose Place? The Moral Geography of Agentic AI for Social Good
Survey of 112 agentic AI for social good papers reveals moral-geographic asymmetry with 73% lacking geographic context (lowest for SDG 16) and only 25% reporting deployments.
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RealUserSim: Bridging the Reality Gap in Agent Benchmarking via Grounded User Simulation
RealUserSim grounds LLM simulators in 7,275 executable profiles from real conversations, raising behavioral match rates from 24.2% to 45.3% and revealing agent failures hidden by cooperative simulators.