25 citations · 58 across the 19 of their papers we have counts for
5 papers · 1 filter
TrojanedCM: A Repository of Trojaned Large Language Models of Code
Aftab Hussain, Md Rafiqul Islam Rabin, Mohammad Amin Alipour
With the rapid growth of research in trojaning deep neural models of source code, we observe that there is a need of developing a benchmark trojaned models for testing various troj…
Occlusion-based Detection of Trojan-triggering Inputs in Large Language Models of Code
Aftab Hussain, Md Rafiqul Islam Rabin, Toufique Ahmed +2
Large language models (LLMs) are becoming an integrated part of software development. These models are trained on large datasets for code, where it is hard to verify each data poin…
A Survey of Trojans in Neural Models of Source Code: Taxonomy and Techniques
Aftab Hussain, Md Rafiqul Islam Rabin, Toufique Ahmed +4
In this work, we study literature in Explainable AI and Safe AI to understand poisoning of neural models of code. In order to do so, we first establish a novel taxonomy for Trojan…
A Study of Variable-Role-based Feature Enrichment in Neural Models of Code
Aftab Hussain, Md Rafiqul Islam Rabin, Bowen Xu +2
Although deep neural models substantially reduce the overhead of feature engineering, the features readily available in the inputs might significantly impact training cost and the…
Study of Distractors in Neural Models of Code
Md Rafiqul Islam Rabin, Aftab Hussain, Sahil Suneja +1
Finding important features that contribute to the prediction of neural models is an active area of research in explainable AI. Neural models are opaque and finding such features sh…