Holy Cross Dr, Notre Dame

Frank Liu

Advanced
@franciscoliu

Computer Science PhD Student at University of Notre Dame. An optimist and always has passion towards coding.

franciscoliu.github.io/

Awesome-GenAI-Unlearning.

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MLLMU-Bench. [NAACL 2025 Main] Official Implementation of MLLMU-Bench

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graphprompter. Implementation of GraphPrompter (The Web Conference 2024 Short Paper)

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SKU. Official code implementation of SKU, Accepted by ACL 2024 Findings

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MANU. [ACL 2025 Main] Official Repo for Modality-Aware Neuron Pruning for Unlearning in Multimodal Large Language Models

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GFAME. Code for Paper fair graph representation learning via diverse mixture-of-experts, WWW 2023

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MTMCS-Bench. Python

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Customer_churning. Customer attrition or “churning” (i.e., more and more customers are leaving their credit card services, such as canceling the cards) is an important problem faced by credit card companies. In this project, you are given a dataset of 10,000 customers with 18 attributes/features, such as, age, salary, marital status, credit card limit, credit card category, and so on. The goal is to build a model that can accurately predict churning customers and help understand the reason behind the scene. The 5-fold cross-validation results will be used in evaluating the performance.

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