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Profile Generation

Profile Generation is the task of creating a profile for an individual or entity based on information about them. The goal of profile generation is to gather as much relevant information about the individual or entity as possible, in order to build an accurate and comprehensive profile.

Papers

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Showing 1–10 of 18 papers

TitleStatusHype
Hierarchical Interaction Summarization and Contrastive Prompting for Explainable Recommendations—0
LettinGo: Explore User Profile Generation for Recommendation System—0
Can LLM-Driven Hard Negative Sampling Empower Collaborative Filtering? Findings and PotentialsCode1
Automating Personalization: Prompt Optimization for Recommendation Reranking—0
Bursting Filter Bubble: Enhancing Serendipity Recommendations with Aligned Large Language Models—0
User Profile with Large Language Models: Construction, Updating, and Benchmarking—0
Solving the Content Gap in Roblox Game Recommendations: LLM-Based Profile Generation and Reranking—0
A Prompting-Based Representation Learning Method for Recommendation with Large Language Models—0
Guided Profile Generation Improves Personalization with LLMs—0
A Flow-Based Model for Conditional and Probabilistic Electricity Consumption Profile Generation and PredictionCode0
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