Human Understanding
Human understanding, a multifaceted field encompassing cognitive processes and AI model capabilities, seeks to unravel how humans and machines comprehend information. Current research focuses on improving AI's ability to understand nuanced language, visual information, and complex relationships within data, employing techniques like multimodal large language models, hypergraph attention networks, and retrieval-augmented generation. These advancements have implications for various applications, including improved medical diagnosis, enhanced human-computer interaction, and more effective scientific knowledge extraction, but challenges remain in achieving truly robust and generalizable understanding in AI.
Papers
The Debate Over Understanding in AI's Large Language Models
Melanie Mitchell, David C. Krakauer
"John is 50 years old, can his son be 65?" Evaluating NLP Models' Understanding of Feasibility
Himanshu Gupta, Neeraj Varshney, Swaroop Mishra, Kuntal Kumar Pal, Saurabh Arjun Sawant, Kevin Scaria, Siddharth Goyal, Chitta Baral
Understanding and Improving Zero-shot Multi-hop Reasoning in Generative Question Answering
Zhengbao Jiang, Jun Araki, Haibo Ding, Graham Neubig
Towards Understanding and Boosting Adversarial Transferability from a Distribution Perspective
Yao Zhu, Yuefeng Chen, Xiaodan Li, Kejiang Chen, Yuan He, Xiang Tian, Bolun Zheng, Yaowu Chen, Qingming Huang
Understanding of the properties of neural network approaches for transient light curve approximations
Mariia Demianenko, Konstantin Malanchev, Ekaterina Samorodova, Mikhail Sysak, Aleksandr Shiriaev, Denis Derkach, Mikhail Hushchyn
Machine Reading, Fast and Slow: When Do Models "Understand" Language?
Sagnik Ray Choudhury, Anna Rogers, Isabelle Augenstein
Probing for Understanding of English Verb Classes and Alternations in Large Pre-trained Language Models
David K. Yi, James V. Bruno, Jiayu Han, Peter Zukerman, Shane Steinert-Threlkeld
Testing Pre-trained Language Models' Understanding of Distributivity via Causal Mediation Analysis
Pangbo Ban, Yifan Jiang, Tianran Liu, Shane Steinert-Threlkeld