Raha Moraffah

According to our database, Raha Moraffah authored at least 30 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

EAGLE: A Domain Generalization Framework for AI-generated Text Detection.

Amrita Bhattacharjee, Raha Moraffah, Joshua Garland, Huan Liu

CoRR, 2024

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

Tharindu Kumarage, Garima Agrawal, Paras Sheth, Raha Moraffah, Aman Chadha, Joshua Garland, Huan Liu

CoRR, 2024

The Wolf Within: Covert Injection of Malice into MLLM Societies via an MLLM Operative.

Zhen Tan, Chengshuai Zhao, Raha Moraffah, Yifan Li, Yu Kong, Tianlong Chen, Huan Liu

CoRR, 2024

Adversarial Text Purification: A Large Language Model Approach for Defense.

Raha Moraffah, Shubh Khandelwal, Amrita Bhattacharjee, Huan Liu

CoRR, 2024

A Generative Approach to Surrogate-based Black-box Attacks.

Raha Moraffah, Huan Liu

CoRR, 2024

Causal Feature Selection for Responsible Machine Learning.

Raha Moraffah, Paras Sheth, Saketh Vishnubhatla, Huan Liu

CoRR, 2024

Exploiting Class Probabilities for Black-box Sentence-level Attacks.

Raha Moraffah, Huan Liu

CoRR, 2024

Causality Guided Disentanglement for Cross-Platform Hate Speech Detection.

Paras Sheth, Raha Moraffah, Tharindu S. Kumarage, Aman Chadha, Huan Liu

Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

2023

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

Suraj Jyothi Unni, Raha Moraffah, Huan Liu

CoRR, 2023

LLMs as Counterfactual Explanation Modules: Can ChatGPT Explain Black-box Text Classifiers?

Amrita Bhattacharjee, Raha Moraffah, Joshua Garland, Huan Liu

CoRR, 2023

PEACE: Cross-Platform Hate Speech Detection - A Causality-Guided Framework.

Paras Sheth, Tharindu Kumarage, Raha Moraffah, Aman Chadha, Huan Liu

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Socially Responsible Machine Learning: A Causal Perspective.

Raha Moraffah, Amir-Hossein Karimi, Adrienne Raglin, Huan Liu

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

ConDA: Contrastive Domain Adaptation for AI-generated Text Detection.

Amrita Bhattacharjee, Tharindu Kumarage, Raha Moraffah, Huan Liu

Proceedings of the 13th International Joint Conference on Natural Language Processing and the 3rd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics, 2023

How Reliable Are AI-Generated-Text Detectors? An Assessment Framework Using Evasive Soft Prompts.

Tharindu Kumarage, Paras Sheth, Raha Moraffah, Joshua Garland, Huan Liu

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Data Integrity and Artificial Reasoning.

Adrienne Raglin, Raha Moraffah

Proceedings of the 5th IEEE International Conference on Cognitive Machine Intelligence, 2023

2022

Evaluation Methods and Measures for Causal Learning Algorithms.

Lu Cheng, Ruocheng Guo, Raha Moraffah, Paras Sheth, K. Selçuk Candan, Huan Liu

IEEE Trans. Artif. Intell., 2022

Domain Generalization - A Causal Perspective.

Paras Sheth, Raha Moraffah, K. Selçuk Candan, Adrienne Raglin, Huan Liu

CoRR, 2022

Query-Efficient Target-Agnostic Black-Box Attack.

Raha Moraffah, Huan Liu

Proceedings of the IEEE International Conference on Data Mining, 2022

Exploring the Target Distribution for Surrogate-Based Black-Box Attacks.

Raha Moraffah, Paras Sheth, Huan Liu

Proceedings of the IEEE International Conference on Big Data, 2022

2021

Causal inference for time series analysis: problems, methods and evaluation.

Raha Moraffah, Paras Sheth, Mansooreh Karami, Anchit Bhattacharya, Qianru Wang, Anique Tahir, Adrienne Raglin, Huan Liu

Knowl. Inf. Syst., 2021

2020

Causal Interpretability for Machine Learning - Problems, Methods and Evaluation.

Raha Moraffah, Mansooreh Karami, Ruocheng Guo, Adrienne Raglin, Huan Liu

SIGKDD Explor., 2020

Use of Bayesian Nonparametric methods for Estimating the Measurements in High Clutter.

Bahman Moraffah, Christ Richmond, Raha Moraffah, Antonia Papandreou-Suppappola

CoRR, 2020

CAN: A Causal Adversarial Network for Learning Observational and Interventional Distributions.

Raha Moraffah, Bahman Moraffah, Mansooreh Karami, Adrienne Raglin, Huan Liu

CoRR, 2020

Causality and Uncertainty of Information for Content Understanding.

Adrienne Raglin, Raha Moraffah, Huan Liu

Proceedings of the 2nd IEEE International Conference on Cognitive Machine Intelligence, 2020

METRIC-Bayes: Measurements Estimation for Tracking in High Clutter using Bayesian Nonparametrics.

Bahman Moraffah, Christ Richmond, Raha Moraffah, Antonia Papandreou-Suppappola

Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020

2019

Deep causal representation learning for unsupervised domain adaptation.

Raha Moraffah, Kai Shu, Adrienne Raglin, Huan Liu

CoRR, 2019

A Practical Data Repository for Causal Learning with Big Data.

Lu Cheng, Ruocheng Guo, Raha Moraffah, K. Selçuk Candan, Adrienne Raglin, Huan Liu

Proceedings of the Benchmarking, Measuring, and Optimizing, 2019

2018

Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects.

Vineeth Rakesh, Ruocheng Guo, Raha Moraffah, Nitin Agarwal, Huan Liu

Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

2017

Hippo in Action: Scalable Indexing of a Billion New York City Taxi Trips and Beyond.

Jia Yu, Raha Moraffah, Mohamed Sarwat

Proceedings of the 33rd IEEE International Conference on Data Engineering, 2017

Database System Support for Personalized Recommendation Applications.

Mohamed Sarwat, Raha Moraffah, Mohamed F. Mokbel, James L. Avery

Proceedings of the 33rd IEEE International Conference on Data Engineering, 2017