activity
20192023
most citedPrompting Frameworks for Large Language Models: A Survey

15 citations · 18 across the 2 of their papers we have counts for

collaborators

5 papers

cs.SE202315 cited

Prompting Frameworks for Large Language Models: A Survey

Xiaoxia Liu, Jingyi Wang, Jun Sun +5

Since the launch of ChatGPT, a powerful AI Chatbot developed by OpenAI, large language models (LLMs) have made significant advancements in both academia and industry, bringing abou…

cs.LG20213 cited

Automatic Fairness Testing of Neural Classifiers through Adversarial Sampling

Peixin Zhang, Jingyi Wang, Jun Sun +5

Although deep learning has demonstrated astonishing performance in many applications, there are still concerns about its dependability. One desirable property of deep learning appl…

cs.LG2020

Towards Repairing Neural Networks Correctly

Guoliang Dong, Jun Sun, Jingyi Wang +2

Neural networks are increasingly applied to support decision making in safety-critical applications (like autonomous cars, unmanned aerial vehicles and face recognition based authe…

cs.LG2019

Towards Interpreting Recurrent Neural Networks through Probabilistic Abstraction

Guoliang Dong, Jingyi Wang, Jun Sun +5

Neural networks are becoming a popular tool for solving many real-world problems such as object recognition and machine translation, thanks to its exceptional performance as an end…

cs.LG2019

Adversarial Sample Detection for Deep Neural Network through Model Mutation Testing

Jingyi Wang, Guoliang Dong, Jun Sun +2

Deep neural networks (DNN) have been shown to be useful in a wide range of applications. However, they are also known to be vulnerable to adversarial samples. By transforming a nor…