5 citations · 17 across the 8 of their papers we have counts for
9 papers
FinDocMRE: A Benchmark for Document-Level Financial Multimodal Reasoning Evaluation
Jiayong Zhu, Jiangtong Li, Jinru Ding +3
While Large Multimodal Models (LMMs) excel in general visual tasks, their deployment in specialized financial contexts remains insufficient. Existing benchmarks prioritize isolated…
Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers
Dongyi Liu, Jiangtong Li
Graph Neural Networks(GNNs) are vulnerable to backdoor attacks, where adversaries implant malicious triggers to manipulate model predictions. Existing trigger generators are often…
FinLMM-R1: Enhancing Financial Reasoning in LMM through Scalable Data and Reward Design
Kai Lan, Jiayong Zhu, Jiangtong Li +3
Large Multimodal Models (LMMs) demonstrate significant cross-modal reasoning capabilities. However, financial applications face challenges due to the lack of high-quality multimoda…
CFBenchmark-MM: Chinese Financial Assistant Benchmark for Multimodal Large Language Model
Jiangtong Li, Yiyun Zhu, Dawei Cheng +2
Multimodal Large Language Models (MLLMs) have rapidly evolved with the growth of Large Language Models (LLMs) and are now applied in various fields. In finance, the integration of…
Attack by Yourself: Effective and Unnoticeable Multi-Category Graph Backdoor Attacks with Subgraph Triggers Pool
Jiangtong Li, Dungy Liu, Dawei Cheng +1
\textbf{G}raph \textbf{N}eural \textbf{N}etworks~(GNNs) have achieved significant success in various real-world applications, including social networks, finance systems, and traffi…
Adaptive Multi-Scale Decomposition Framework for Time Series Forecasting
Yifan Hu, Peiyuan Liu, Peng Zhu +2
Transformer-based and MLP-based methods have emerged as leading approaches in time series forecasting (TSF). While Transformer-based methods excel in capturing long-range dependenc…
Multi-Patch Prediction: Adapting LLMs for Time Series Representation Learning
Yuxuan Bian, Xuan Ju, Jiangtong Li +3
In this study, we present aLLM4TS, an innovative framework that adapts Large Language Models (LLMs) for time-series representation learning. Central to our approach is that we reco…
CFBenchmark: Chinese Financial Assistant Benchmark for Large Language Model
Yang Lei, Jiangtong Li, Dawei Cheng +2
Large language models (LLMs) have demonstrated great potential in the financial domain. Thus, it becomes important to assess the performance of LLMs in the financial tasks. In this…
CFGPT: Chinese Financial Assistant with Large Language Model
Jiangtong Li, Yuxuan Bian, Guoxuan Wang +4
Large language models (LLMs) have demonstrated great potential in natural language processing tasks within the financial domain. In this work, we present a Chinese Financial Genera…