7 papers
Large Language Models for Few-Shot Named Entity Recognition
Yufei Zhao, Xiaoshi Zhong, Erik Cambria +1
Named entity recognition (NER) is a fundamental task in numerous downstream applications. Recently, researchers have employed pre-trained language models (PLMs) and large language…
GPTEval: A Survey on Assessments of ChatGPT and GPT-4
Rui Mao, Guanyi Chen, Xulang Zhang +2
The emergence of ChatGPT has generated much speculation in the press about its potential to disrupt social and economic systems. Its astonishing language ability has aroused strong…
Are Large Language Models Really Good Logical Reasoners? A Comprehensive Evaluation and Beyond
Fangzhi Xu, Qika Lin, Jiawei Han +3
Logical reasoning consistently plays a fundamental and significant role in the domains of knowledge engineering and artificial intelligence. Recently, Large Language Models (LLMs)…
Negation Blindness in Large Language Models: Unveiling the NO Syndrome in Image Generation
Mohammad Nadeem, Shahab Saquib Sohail, Erik Cambria +2
Foundational Large Language Models (LLMs) have changed the way we perceive technology. They have been shown to excel in tasks ranging from poem writing and coding to essay generati…
EnTri: Ensemble Learning with Tri-level Representations for Explainable Scene Recognition
Amirhossein Aminimehr, Amirali Molaei, Erik Cambria
Scene recognition based on deep-learning has made significant progress, but there are still limitations in its performance due to challenges posed by inter-class similarities and i…
TbExplain: A Text-based Explanation Method for Scene Classification Models with the Statistical Prediction Correction
Amirhossein Aminimehr, Pouya Khani, Amirali Molaei +2
The field of Explainable Artificial Intelligence (XAI) aims to improve the interpretability of black-box machine learning models. Building a heatmap based on the importance value o…