4 papers
WIN-U: Woodbury-Informed Newton-Unlearning as a retain-free Machine Unlearning Framework
Xingjian Zhao, Mohammad Mohammadi Amiri, Malik Magdon-Ismail
Privacy concerns in LLMs have led to the rapidly growing need to enforce a data's "right to be forgotten". Machine unlearning addresses precisely this task, namely the removal of t…
Open FinLLM Leaderboard: Towards Financial AI Readiness
Shengyuan Colin Lin, Felix Tian, Keyi Wang +9
Financial large language models (FinLLMs) with multimodal capabilities are envisioned to revolutionize applications across business, finance, accounting, and auditing. However, rea…
Reinforcement Learning for Quantum Circuit Design: Using Matrix Representations
Zhiyuan Wang, Chunlin Feng, Christopher Poon +5
Quantum computing promises advantages over classical computing. The manufacturing of quantum hardware is in the infancy stage, called the Noisy Intermediate-Scale Quantum (NISQ) er…
FinLoRA: Finetuning Quantized Financial Large Language Models Using Low-Rank Adaptation
Dannong Wang, Daniel Kim, Bo Jin +4
Finetuned large language models (LLMs) have shown remarkable performance in financial tasks, such as sentiment analysis and information retrieval. Due to privacy concerns, finetuni…