6 papers
MMLDSum-LLM: Multimodal Long-Document Summarization with Visual-Alignment and Keyword-Aware
Xianpeng Zhang, Jiahua Yang, Dongyu Chen +7
The paper presents a benchmark for multimodal long-document summarization and a two-stage training framework (MMLDSum-LLM) that incorporates visual-alignment and keyword-aware loss…
QuantEval: A Benchmark for Financial Quantitative Tasks in Large Language Models
Zhaolu Kang, Junhao Gong, Wenqing Hu +15
Large Language Models (LLMs) have shown strong capabilities across many domains, yet their evaluation in financial quantitative tasks remains fragmented and mostly limited to knowl…
Learning from Prompt itself: the Hierarchical Attribution Prompt Optimization
Dongyu Chen, Jian Ma, Xianpeng Zhang +5
Optimization is fundamental across numerous disciplines, typically following an iterative process of refining an initial solution to enhance performance. This principle is equally…
Easy Adaptation: An Efficient Task-Specific Knowledge Injection Method for Large Models in Resource-Constrained Environments
Dong Chen, Zhengqing Hu, Shixing Zhao +1
While the enormous parameter scale endows Large Models (LMs) with unparalleled performance, it also limits their adaptability across specific tasks. Parameter-Efficient Fine-Tuning…
MIMO: A medical vision language model with visual referring multimodal input and pixel grounding multimodal output
Yanyuan Chen, Dexuan Xu, Yu Huang +6
Currently, medical vision language models are widely used in medical vision question answering tasks. However, existing models are confronted with two issues: for input, the model…
TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning
Chengkai Xu, Jiaqi Liu, Shiyu Fang +4
Although Deep Reinforcement Learning (DRL) and Large Language Models (LLMs) each show promise in addressing decision-making challenges in autonomous driving, DRL often suffers from…