ConSearcher generates query-based member personas in an LLM conversational tool, yielding higher information-seeking outcomes and engagement than baselines in a 27-person study, with noted risks of over-personalization.
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A new framework evaluates utility of synthetic mobility trajectories while a membership inference attack reveals privacy vulnerabilities in generative models thought to be safe.
PGHS fuses policy-guided LLM reasoning and ML fitting to simulate group user behavior with 8.8% error on Meituan data from 101 merchants and 26k trajectories, beating pure reasoning and fitting baselines by 45.8% and 40.9%.
SubFlow restores full mode coverage in one-step flow matching by conditioning on sub-modes from semantic clustering, yielding higher diversity on ImageNet-256 while preserving FID.
citing papers explorer
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ConSearcher: Supporting Conversational Information Seeking in Online Communities with Member Personas
ConSearcher generates query-based member personas in an LLM conversational tool, yielding higher information-seeking outcomes and engagement than baselines in a 27-person study, with noted risks of over-personalization.
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A Dual Perspective on Synthetic Trajectory Generators: Utility Framework and Privacy Vulnerabilities
A new framework evaluates utility of synthetic mobility trajectories while a membership inference attack reveals privacy vulnerabilities in generative models thought to be safe.
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Meituan Merchant Business Diagnosis via Policy-Guided Dual-Process User Simulation
PGHS fuses policy-guided LLM reasoning and ML fitting to simulate group user behavior with 8.8% error on Meituan data from 101 merchants and 26k trajectories, beating pure reasoning and fitting baselines by 45.8% and 40.9%.
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SubFlow: Sub-mode Conditioned Flow Matching for Diverse One-Step Generation
SubFlow restores full mode coverage in one-step flow matching by conditioning on sub-modes from semantic clustering, yielding higher diversity on ImageNet-256 while preserving FID.