most citedHARMONIC: Harnessing LLMs for Tabular Data Synthesis and Privacy Protection

4 citations · 4 across the 1 of their papers we have counts for

collaborators

5 papers

cs.LG20244 cited

HARMONIC: Harnessing LLMs for Tabular Data Synthesis and Privacy Protection

Yuxin Wang, Duanyu Feng, Yongfu Dai +5

Data serves as the fundamental foundation for advancing deep learning, particularly tabular data presented in a structured format, which is highly conducive to modeling. However, e…

cs.CL2024

Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications

Jimin Huang, Mengxi Xiao, Dong Li +41

Financial LLMs hold promise for advancing financial tasks and domain-specific applications. However, they are limited by scarce corpora, weak multimodal capabilities, and narrow ev…

cs.CL2024

FinBen: A Holistic Financial Benchmark for Large Language Models

Qianqian Xie, Weiguang Han, Zhengyu Chen +31

LLMs have transformed NLP and shown promise in various fields, yet their potential in finance is underexplored due to a lack of comprehensive evaluation benchmarks, the rapid devel…

cs.CL2023

LAiW: A Chinese Legal Large Language Models Benchmark

Yongfu Dai, Duanyu Feng, Jimin Huang +6

General and legal domain LLMs have demonstrated strong performance in various tasks of LegalAI. However, the current evaluations of these LLMs in LegalAI are defined by the experts…

cs.LG2023

Empowering Many, Biasing a Few: Generalist Credit Scoring through Large Language Models

Duanyu Feng, Yongfu Dai, Jimin Huang +6

In the financial industry, credit scoring is a fundamental element, shaping access to credit and determining the terms of loans for individuals and businesses alike. Traditional cr…