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Large Language Models for User Modeling (LLM-UM) Reading List

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This repository contains a list of papers on large language models for user modeling (LLM-UM) based on our survey paper: User Modeling in the Era of Large Language Models: Current Research and Future Directions (Zhaoxuan Tan and Meng Jiang). We categorize existing works based on their approaches and applications.

We will try to make this list updated. If you find any error or any missed paper, please don't hesitate to open an issue or pull request.

<div align="center"> <img src="./asset/intro.png" width="70%" height="50%"> </div>

Motivation: Why LLMs for User Modeling?

<div align="center"> <img src="./asset/LLM-UM_Fig2.png" width="100%" height="50%"> </div>

LLMs have shown promising potential in modeling and comprehending user-generated content (UGC), as evidenced by various studies and examples. One area of focus is utilizing LLMs for recommendation purposes, where they can predict users' item-based interests based on their behavior history. User profiling is another domain where LLMs excel, summarizing users' characteristics and interests from their generated content and history. In the context of rating prediction, LLMs can leverage reasoning based on users' previous ratings to predict ratings for candidate items. Additionally, LLMs demonstrate the ability to understand user personality and recognize it based on UGC history. They also prove effective in detecting suspicious UGC, such as hate speech. These findings collectively illustrate the capabilities of LLMs in modeling, understanding, and reasoning UGC and user behavior, making them valuable tools for user-oriented applications.

Approaches to LLM-UM

LLMs as Predictors

<div align="center"> <img src="./asset/LLM-UM_Predictors.png" width="100%" height="70%"> </div>

Common Generative Reasoner

Simulator/Agent

Classifier/Detector

Scoring Function

Explainer

Chatbot

LLMs as Enhancer

Profiler

Feature Encoder

<div align="center"> <img src="./asset/LLM-UM_Enhancers.png" width="100%" height="70%"> </div>

Knowledge Augmenter

Data Generator

<div align="center"> <img src="./asset/LLM-UM_controller_evaluator.png" width="100%" height="70%"> </div>

LLMs as Controllers

LLMs as Evaluators

Applications of LLM-UM

Personalization

User Profiling

Personalized Recommendation

Top-k Recommendation

Rating Prediction

Conversational Recommendation

Persoanlized Assistance

Personalized Dialogue System

Personalized Education

Personalized Healthcare

Suspiciousness Detection

Fraud Detection

Discrimination Detection

Misinformation Detection

LLM-Generated Text Detection

Contributing

🧐 Contributions to this repository are welcome!

If you have come across relevant resources, feel free to open an issue or submit a pull request.

- **paper_name [[link]](paper_link)**

Citation

If you find this repository helpful for your work, please kindly cite our paper.

@article{tan2023user,
  title={User Modeling in the Era of Large Language Models: Current Research and Future Directions},
  author={Tan, Zhaoxuan and Jiang, Meng},
  journal={IEEE Data Engineering Bulletin},
  year={2023}
}

Acknowledgement

This page is contributed by Zhaoxuan Tan (ztan3@nd.edu) and Meng Jiang (mjiang2@nd.edu).