#personalization
7 papers match
Contextualized Counterspeech Can Be More Persuasive Than Generic Counterspeech
Lorenzo Cima, Alessio Miaschi, Amaury Trujillo +3
The paper investigates AI‑generated counterspeech that is adapted to the conversation and the target user, showing that lightweight contextual and personalization strategies can im…
Supervised Fine-Tuning vs. In-Context Learning: An Equilibrium Analysis of LLM Personalization under Congestion
Fengzhuo Zhang, Zhuoran Yang, Dirk Bergemann
The paper studies when users of large language models should use expensive supervised fine-tuning versus lightweight in‑context learning, considering how other users' choices creat…
Toward Metaphor-Fluid Conversation Design for Voice User Interfaces
Smit Desai, Jessie Chin, Dakuo Wang +2
The paper proposes Metaphor-Fluid Design, a method that dynamically changes metaphorical representations in voice user interfaces to match different conversational contexts, and sh…
DRIFTLENS: Measuring Memory-Induced Reasoning Drift in Personalized Language Models
Xi Fang, Weijie Xu, Yingqiang Ge +3
The paper introduces DRIFTLENS, a framework for measuring how injecting user-specific memory into personalized language models changes the models' reasoning steps, and evaluates me…
SlimPer: Make Personalization Model Slim and Smart
Siqi Wang, Xianjie Chen, Shaofeng Deng +42
SlimPer is a transformer‑based recommendation model that treats personalized ranking as iterative refinement of a compact user‑item knowledge base, achieving linear per‑layer cost…
Latent-Identity Tuning in Text-to-Image Personalization Models
Daniel Garibi, Ronen Kamenetsky, Hadar Averbuch-Elor +2
The paper introduces a method to fine‑tune the latent representation of a specific face identity within frozen text‑to‑image personalization models, enabling diverse yet identity‑c…