1 citations · 1 across the 6 of their papers we have counts for
7 papers
HIFICL: High-Fidelity In-Context Learning for Multimodal Tasks
Xiaoyu Li, Yuhang Liu, Xuanshuo Kang +4
In-Context Learning (ICL) is a significant paradigm for Large Multimodal Models (LMMs), using a few in-context demonstrations (ICDs) for new task adaptation. However, its performan…
Spider-Sense: Intrinsic Risk Sensing for Efficient Agent Defense with Hierarchical Adaptive Screening
Zhenxiong Yu, Zhi Yang, Zhiheng Jin +19
As large language models (LLMs) evolve into autonomous agents, their real-world applicability has expanded significantly, accompanied by new security challenges. Most existing agen…
UniFinEval: Towards Unified Evaluation of Financial Multimodal Models across Text, Images and Videos
Zhi Yang, Lingfeng Zeng, Fangqi Lou +16
Multimodal large language models are playing an increasingly significant role in empowering the financial domain, however, the challenges they face, such as multimodal and high-den…
VisFinEval: A Scenario-Driven Chinese Multimodal Benchmark for Holistic Financial Understanding
Zhaowei Liu, Xin Guo, Haotian Xia +11
Multimodal large language models (MLLMs) hold great promise for automating complex financial analysis. To comprehensively evaluate their capabilities, we introduce VisFinEval, the…
FinGAIA: A Chinese Benchmark for AI Agents in Real-World Financial Domain
Lingfeng Zeng, Fangqi Lou, Zixuan Wang +18
The booming development of AI agents presents unprecedented opportunities for automating complex tasks across various domains. However, their multi-step, multi-tool collaboration c…
Multiscale Adaptive Conflict-Balancing Model For Multimedia Deepfake Detection
Zihan Xiong, Xiaohua Wu, Lei Chen +1
Advances in computer vision and deep learning have blurred the line between deepfakes and authentic media, undermining multimedia credibility through audio-visual forgery. Current…