4 papers
LA-RL: Label-Aware Self-Reflection for Reinforcement Learning in Information Extraction
Xiao You, Tianwei Yan, Zixu Shan +2
Large language models show strong promise for information extraction (IE), but existing reflection-based correction methods are often misaligned with structured extraction outputs.…
LC-ICL: Label-Guided Contrastive In-Context Learning for Robust Information Extraction
Xiao You, Tianwei Yan, Shan Zhao
There has been increasing interest in exploring the capabilities of advanced large language models (LLMs) in the field of information extraction (IE), specifically focusing on task…
MOSABench: Multi-Object Sentiment Analysis Benchmark for Evaluating Multimodal Large Language Models Understanding of Complex Image
Shezheng Song, Chengxiang He, Shan Zhao +4
Multimodal large language models (MLLMs) have shown remarkable progress in high-level semantic tasks such as visual question answering, image captioning, and emotion recognition. H…
How to Bridge the Gap between Modalities: Survey on Multimodal Large Language Model
Shezheng Song, Xiaopeng Li, Shasha Li +5
We explore Multimodal Large Language Models (MLLMs), which integrate LLMs like GPT-4 to handle multimodal data, including text, images, audio, and more. MLLMs demonstrate capabilit…