Summary of Socfedgpt: Federated Gpt-based Adaptive Content Filtering System Leveraging User Interactions in Social Networks, by Sai Puppala et al.
SocFedGPT: Federated GPT-based Adaptive Content Filtering System Leveraging User Interactions in Social Networks
by Sai Puppala, Ismail Hossain, Md Jahangir Alam, Sajedul Talukder
First submitted to arxiv on: 7 Aug 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Distributed, Parallel, and Cluster Computing (cs.DC); Information Retrieval (cs.IR); Social and Information Networks (cs.SI)
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Summary difficulty | Written by | Summary |
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High | Paper authors | High Difficulty Summary Read the original abstract here |
Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This study develops a novel approach to enhancing user interaction and content relevance in social media platforms through a federated learning framework. The authors introduce personalized GPT and Context-based Social Media LLM models, utilizing federated learning for privacy and security. The approach involves four client entities receiving a base GPT-2 model and locally collected social media data, with federated aggregation ensuring up-to-date model maintenance. Subsequent modules focus on categorizing user posts, computing user persona scores, and identifying relevant posts from friends’ lists. The authors also propose a quantifying social engagement approach, coupled with matrix factorization techniques, to facilitate personalized content suggestions in real-time. Additionally, an adaptive feedback loop and readability score algorithm enhance the quality and relevance of content presented to users. |
Low | GrooveSquid.com (original content) | Low Difficulty Summary This study creates a new way to make social media better by helping people interact and find interesting things to look at. They use special computer models called GPT and LLM to personalize what you see based on your interests. The models are trained using data from four different groups, which helps keep the information up-to-date and private. The study also includes ways to categorize posts, figure out what kind of person someone is, and suggest relevant content. This can help make social media more engaging and fun for users while keeping their personal info safe. |
Keywords
» Artificial intelligence » Federated learning » Gpt