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#user-modeling News & Analysis

4 articles tagged with #user-modeling. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

4 articles
AINeutralarXiv – CS AI · 10h ago6/10
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UxSID: Semantic-Aware User Interests Modeling for Ultra-Long Sequence

UxSID is a new machine learning framework that models long user behavior sequences using semantic grouping and dual-level attention, achieving state-of-the-art performance with a 0.337% revenue lift in large-scale advertising tests. The approach balances computational efficiency with semantic awareness by using Semantic IDs rather than item-specific search methods.

AINeutralarXiv – CS AI · 10h ago6/10
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A Reflective Storytelling Agent for Older Adults: Integrating Argumentation Schemes and Argument Mining in LLM-Based Personalised Narratives

Researchers developed a reflective storytelling agent that combines large language models with knowledge graphs and argumentation theory to generate personalized narratives for older adults. Testing with 55 participants showed the system successfully identified personally relevant purposes in two-thirds of narratives, with argument-based grounding and hallucination detection significantly improving perceived consistency and clarity.

AINeutralarXiv – CS AI · Apr 156/10
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PrivacyReasoner: Can LLM Emulate a Human-like Privacy Mind?

Researchers introduce PrivacyReasoner, an LLM-based agent architecture that reconstructs individual privacy perspectives from online comment history to predict how specific people would perceive data practices. The system outperforms baseline models in predicting privacy concerns across AI, e-commerce, and healthcare domains by contextually activating relevant privacy beliefs.

AIBullisharXiv – CS AI · Mar 175/10
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Iterative Semantic Reasoning from Individual to Group Interests for Generative Recommendation with LLMs

Researchers propose an Iterative Semantic Reasoning Framework (ISRF) that uses large language models to improve recommendation systems by bridging explicit individual user interests with implicit group interests. The framework employs multi-step bidirectional reasoning and iterative optimization to achieve better user interest modeling than existing methods.