Persona-db: Efficient large language model personalization for response prediction with collaborative data refinement

C Sun, K Yang, RG Reddy, YR Fung, HP Chan… - arxiv preprint arxiv …, 2024 - arxiv.org
The increasing demand for personalized interactions with large language models (LLMs)
calls for methodologies capable of accurately and efficiently identifying user opinions and …

Two tales of persona in llms: A survey of role-playing and personalization

YM Tseng, YC Huang, TY Hsiao, YC Hsu… - arxiv preprint arxiv …, 2024 - arxiv.org
Recently, methods investigating how to adapt large language models (LLMs) for specific
scenarios have gained great attention. Particularly, the concept of\textit {persona}, originally …

" It was 80% me, 20% AI": Seeking Authenticity in Co-Writing with Large Language Models

AHC Hwang, QV Liao, SL Blodgett, A Olteanu… - arxiv preprint arxiv …, 2024 - arxiv.org
Given the rising proliferation and diversity of AI writing assistance tools, especially those
powered by large language models (LLMs), both writers and readers may have concerns …

A Comparison of Methods for Evaluating Generative IR

N Arabzadeh, CLA Clarke - arxiv preprint arxiv:2404.04044, 2024 - arxiv.org
Information retrieval systems increasingly incorporate generative components. For example,
in a retrieval augmented generation (RAG) system, a retrieval component might provide a …

SLOWLY DYING OR RESILIENT? REVISITING THE SECI MODEL AFTER 3 DECADES IN THE CONTEXT OF GENERATIVE AI

TT Richter, J Paul, L Wolf, F Boumdine - ICERI2024 Proceedings, 2024 - library.iated.org
This paper aims to revise Nonaka and Takeuchi's SECI (Socialization, Externalization,
Combination, Internalization) Model in light of recent advancements in Generative Artificial …