6 citations · 13 across the 5 of their papers we have counts for
4 papers · 1 filter
MMIDR: Teaching Large Language Model to Interpret Multimodal Misinformation via Knowledge Distillation
Longzheng Wang, Xiaohan Xu, Lei Zhang +5
Automatic detection of multimodal misinformation has gained a widespread attention recently. However, the potential of powerful Large Language Models (LLMs) for multimodal misinfor…
A Boundary Offset Prediction Network for Named Entity Recognition
Minghao Tang, Yongquan He, Yongxiu Xu +3
Named entity recognition (NER) is a fundamental task in natural language processing that aims to identify and classify named entities in text. However, span-based methods for NER t…
Learning to Correct Noisy Labels for Fine-Grained Entity Typing via Co-Prediction Prompt Tuning
Minghao Tang, Yongquan He, Yongxiu Xu +3
Fine-grained entity typing (FET) is an essential task in natural language processing that aims to assign semantic types to entities in text. However, FET poses a major challenge kn…
Re-Reading Improves Reasoning in Large Language Models
Xiaohan Xu, Chongyang Tao, Tao Shen +5
To enhance the reasoning capabilities of off-the-shelf Large Language Models (LLMs), we introduce a simple, yet general and effective prompting method, Re2, i.e., \textbf{Re}-\text…