Anchored Privacy Drifting (APD) replaces privacy-sensitive visual elements with semantically equivalent alternatives while anchoring context, evaluated on the new AdaptShield benchmark with reported gains of 10.4% and 8.5% across four MLLM families.
Evaluation of geolocation capabilities of multimodal large language models and analysis of associated privacy risks.arXiv preprint arXiv:2506.23481, 2025
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ERGeoBench is a new diagnostic benchmark evaluating MLLMs on four capabilities in three progressive embodied geo-localization settings, finding that models handle high-level semantics but struggle with fine-grained perception and metric localization.
OrganicHAR discovers 4-8 activity categories per user from sensor signals, achieves 79% accuracy on coarse activities with ambient sensors alone and cuts VLM queries by 90% by triggering video analysis only at detected pattern moments.
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ERGeoBench:A Comprehensive Benchmark for Embodied Reasoning and Geo-localization in Multimodal Large Language Models
ERGeoBench is a new diagnostic benchmark evaluating MLLMs on four capabilities in three progressive embodied geo-localization settings, finding that models handle high-level semantics but struggle with fine-grained perception and metric localization.