10 citations · 11 across the 9 of their papers we have counts for
5 papers · 1 filter
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…
DIM: Dynamic Integration of Multimodal Entity Linking with Large Language Model
Shezheng Song, Shasha Li, Jie Yu +6
Our study delves into Multimodal Entity Linking, aligning the mention in multimodal information with entities in knowledge base. Existing methods are still facing challenges like a…
PTA: Enhancing Multimodal Sentiment Analysis through Pipelined Prediction and Translation-based Alignment
Shezheng Song, Shasha Li, Shan Zhao +8
Multimodal aspect-based sentiment analysis (MABSA) aims to understand opinions in a granular manner, advancing human-computer interaction and other fields. Traditionally, MABSA met…
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…