PersonaMem

bowen-upenn

[COLM 2025] Know Me, Respond to Me: Benchmarking LLMs for Dynamic User Profiling and Personalized Responses at Scale

benchmark

View on GitHub

135 Stars

8 Forks

135 Watchers

Python Language

mit License

100 SrcLog Score

Cost to Build

$26.30M

Market Value

$80.13M

How is this calculated?

Growth over time

3 data points · 2026-04-11 → 2026-04-26

Stars Forks Watchers

💬

How do you feel about this project?

Ask AI about PersonaMem

Question copied to clipboard

What is the bowen-upenn/PersonaMem GitHub project? Description: "[COLM 2025] Know Me, Respond to Me: Benchmarking LLMs for Dynamic User Profiling and Personalized Responses at Scale". Written in Python. Explain what it does, its main use cases, key features, and who would benefit from using it.

Question is copied to clipboard — paste it after the AI opens.

How to clone PersonaMem

Clone via HTTPS

git clone https://github.com/bowen-upenn/PersonaMem.git

Clone via SSH

[email protected]:bowen-upenn/PersonaMem.git

Download ZIP

Download master.zip

Found an issue?

Report bugs or request features on the PersonaMem issue tracker:

Open GitHub Issues

Similar to PersonaMem

netdata fashion-mnist FrameworkBenchmarks BenchmarkDotNet jmeter awesome-semantic-segmentation sysbench hyperfine tsung benchmark_results across web-frameworks php-framework-benchmark jsperf.com go-web-framework-benchmark huststore phoronix-test-suite Attabench ann-benchmarks sbt-jmh caffenet-benchmark chillout IocPerformance prophiler TBCF NBench sympact awesome-http-benchmark BlurTestAndroid pytest-benchmark