4 citations · 6 across the 3 of their papers we have counts for
6 papers
Can Large Models Fool the Eye? A New Turing Test for Biological Animation
Zijian Chen, Lirong Deng, Zhengyu Chen +5
Evaluating the abilities of large models and manifesting their gaps are challenging. Current benchmarks adopt either ground-truth-based score-form evaluation on static datasets or…
Retrieval-augmented Large Language Models for Financial Time Series Forecasting
Mengxi Xiao, Zihao Jiang, Lingfei Qian +10
Accurately forecasting stock price movements is critical for informed financial decision-making, supporting applications ranging from algorithmic trading to risk management. Howeve…
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…
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…
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…
PIE: Simulating Disease Progression via Progressive Image Editing
Kaizhao Liang, Xu Cao, Kuei-Da Liao +6
Disease progression simulation is a crucial area of research that has significant implications for clinical diagnosis, prognosis, and treatment. One major challenge in this field i…