arXiv AI By Rebecca M. M. Hicke, Kiran Tomlinson

Adopt $\neq$ Adapt: Longitudinal Analyses of LLM Conversations in the Wild

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arXiv AI
Aug 7

LUNAR: Benchmarking Personalized Large Language Models on UNiversal User BehAvioR Logs

arXiv:2608. 05246v1 Announce Type: new Abstract: Existing personalized LLM benchmarks primarily rely on textual personas or isolated behavioral signals, providing limited evaluation of cross-domain behavioral personalization, where responses must be grounded in heterogeneous daily-life activities.

By Jiahao Zhang, Yongzhi Tong, Zelin Fu, Pengde Zhao, Yanmei Jiang, Jiang Feng, Min Yang
arXiv Computation and Language
Aug 25

PersonaMem-v3: Toward Omni-Platform Personal Intelligence for Holistic User Understanding, Recommendation, and Agentic Tasks

PersonaMem-v3 is a benchmark and evaluation harness designed to assess omni-platform personal intelligence for AI agents. It is built from over one million anonymized real-world engagement histories, covering social media, chatbots, calendars, and AI companions, and tracks user preferences and habits over time. The benchmark tests agents on personalization, LLM-powered recommendation, proactiveness, agentic tool use, and geo-temporal reasoning, evaluating their ability to infer holistic user understanding, personalize responses, rerank recommendations, follow user steering, and avoid inappropriate personalization.

By Bowen Jiang, Yuan Yuan, Zhuoqun Hao, Yuchen Liu, Maohao Shen, Sihao Chen, Gregory Wornell, Chris Callison-Burch, Lyle Ungar, Dan Roth, Qi Guo, Xiangjun Fan, Camillo J. Taylor, Hanchao Yu