most citedA Survey of AI-generated Text Forensic Systems: Detection, Attribution, and Characterization

3 citations · 6 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG20241 cited

Cross-Platform Hate Speech Detection with Weakly Supervised Causal Disentanglement

Paras Sheth, Tharindu Kumarage, Raha Moraffah +2

Content moderation faces a challenging task as social media's ability to spread hate speech contrasts with its role in promoting global connectivity. With rapidly evolving slang an…

cs.CL20243 cited

A Survey of AI-generated Text Forensic Systems: Detection, Attribution, and Characterization

Tharindu Kumarage, Garima Agrawal, Paras Sheth +4

We have witnessed lately a rapid proliferation of advanced Large Language Models (LLMs) capable of generating high-quality text. While these LLMs have revolutionized text generatio…

cs.CL2024

Exploiting Class Probabilities for Black-box Sentence-level Attacks

Raha Moraffah, Huan Liu

Sentence-level attacks craft adversarial sentences that are synonymous with correctly-classified sentences but are misclassified by the text classifiers. Under the black-box settin…

cs.LG2024

A Generative Approach to Surrogate-based Black-box Attacks

Raha Moraffah, Huan Liu

Surrogate-based black-box attacks have exposed the heightened vulnerability of DNNs. These attacks are designed to craft adversarial examples for any samples with black-box target…

cs.LG20241 cited

Causal Feature Selection for Responsible Machine Learning

Raha Moraffah, Paras Sheth, Saketh Vishnubhatla +1

Machine Learning (ML) has become an integral aspect of many real-world applications. As a result, the need for responsible machine learning has emerged, focusing on aligning ML mod…

cs.CV2023

VQA-GEN: A Visual Question Answering Benchmark for Domain Generalization

Suraj Jyothi Unni, Raha Moraffah, Huan Liu

Visual question answering (VQA) models are designed to demonstrate visual-textual reasoning capabilities. However, their real-world applicability is hindered by a lack of comprehen…