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ORCIDRaha Moraffah
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2020 – today
- 2024
[c17]Saketh Vishnubhatla, Adrienne Raglin, Raha Moraffah, Huan Liu:
Causal Inductive Biases for Cognitive Machine Learning. CogMI 2024: 14-16- [c16]Zhen Tan, Chengshuai Zhao, Raha Moraffah, Yifan Li, Song Wang, Jundong Li, Tianlong Chen, Huan Liu:
Glue pizza and eat rocks - Exploiting Vulnerabilities in Retrieval-Augmented Generative Models. EMNLP 2024: 1610-1626 - [c15]Raha Moraffah
, Shubh Khandelwal, Amrita Bhattacharjee, Huan Liu:
Adversarial Text Purification: A Large Language Model Approach for Defense. PAKDD (5) 2024: 65-77 - [c14]Paras Sheth, Raha Moraffah, Tharindu S. Kumarage, Aman Chadha, Huan Liu:
Causality Guided Disentanglement for Cross-Platform Hate Speech Detection. WSDM 2024: 626-635 - [i24]Raha Moraffah, Huan Liu:
Exploiting Class Probabilities for Black-box Sentence-level Attacks. CoRR abs/2402.02695 (2024) - [i23]Raha Moraffah, Paras Sheth, Saketh Vishnubhatla, Huan Liu:
Causal Feature Selection for Responsible Machine Learning. CoRR abs/2402.02696 (2024) - [i22]Raha Moraffah, Huan Liu:
A Generative Approach to Surrogate-based Black-box Attacks. CoRR abs/2402.02732 (2024) - [i21]Raha Moraffah, Shubh Khandelwal, Amrita Bhattacharjee, Huan Liu:
Adversarial Text Purification: A Large Language Model Approach for Defense. CoRR abs/2402.06655 (2024) - [i20]Zhen Tan, Chengshuai Zhao, Raha Moraffah, Yifan Li, Yu Kong, Tianlong Chen, Huan Liu:
The Wolf Within: Covert Injection of Malice into MLLM Societies via an MLLM Operative. CoRR abs/2402.14859 (2024) - [i19]Tharindu Kumarage, Garima Agrawal, Paras Sheth, Raha Moraffah, Aman Chadha, Joshua Garland, Huan Liu:
A Survey of AI-generated Text Forensic Systems: Detection, Attribution, and Characterization. CoRR abs/2403.01152 (2024) - [i18]Amrita Bhattacharjee, Raha Moraffah, Joshua Garland, Huan Liu:
EAGLE: A Domain Generalization Framework for AI-generated Text Detection. CoRR abs/2403.15690 (2024) - [i17]Paras Sheth, Tharindu Kumarage, Raha Moraffah, Aman Chadha, Huan Liu:
Cross-Platform Hate Speech Detection with Weakly Supervised Causal Disentanglement. CoRR abs/2404.11036 (2024) - [i16]Amrita Bhattacharjee, Raha Moraffah, Joshua Garland, Huan Liu:
Zero-shot LLM-guided Counterfactual Generation for Text. CoRR abs/2405.04793 (2024) - [i15]Zhen Tan, Chengshuai Zhao, Raha Moraffah, Yifan Li, Song Wang, Jundong Li, Tianlong Chen, Huan Liu:
"Glue pizza and eat rocks" - Exploiting Vulnerabilities in Retrieval-Augmented Generative Models. CoRR abs/2406.19417 (2024) - 2023
- [c13]Adrienne Raglin, Raha Moraffah:
Data Integrity and Artificial Reasoning. CogMI 2023: 93-96 - [c12]Tharindu Kumarage, Paras Sheth, Raha Moraffah, Joshua Garland, Huan Liu:
How Reliable Are AI-Generated-Text Detectors? An Assessment Framework Using Evasive Soft Prompts. EMNLP (Findings) 2023: 1337-1349 - [c11]Amrita Bhattacharjee, Tharindu Kumarage, Raha Moraffah, Huan Liu:
ConDA: Contrastive Domain Adaptation for AI-generated Text Detection. IJCNLP (1) 2023: 598-610 - [c10]Raha Moraffah, Amir-Hossein Karimi, Adrienne Raglin, Huan Liu:
Socially Responsible Machine Learning: A Causal Perspective. KDD 2023: 5819-5820 - [c9]Paras Sheth, Tharindu Kumarage, Raha Moraffah, Aman Chadha, Huan Liu:
PEACE: Cross-Platform Hate Speech Detection - A Causality-Guided Framework. ECML/PKDD (1) 2023: 559-575 - [i14]Paras Sheth, Tharindu Kumarage, Raha Moraffah, Aman Chadha, Huan Liu:
PEACE: Cross-Platform Hate Speech Detection- A Causality-guided Framework. CoRR abs/2306.08804 (2023) - [i13]Paras Sheth, Tharindu Kumarage, Raha Moraffah, Aman Chadha, Huan Liu:
Causality Guided Disentanglement for Cross-Platform Hate Speech Detection. CoRR abs/2308.02080 (2023) - [i12]Amrita Bhattacharjee, Tharindu Kumarage, Raha Moraffah, Huan Liu:
ConDA: Contrastive Domain Adaptation for AI-generated Text Detection. CoRR abs/2309.03992 (2023) - [i11]Amrita Bhattacharjee, Raha Moraffah, Joshua Garland, Huan Liu:
LLMs as Counterfactual Explanation Modules: Can ChatGPT Explain Black-box Text Classifiers? CoRR abs/2309.13340 (2023) - [i10]Tharindu Kumarage, Paras Sheth, Raha Moraffah, Joshua Garland, Huan Liu:
How Reliable Are AI-Generated-Text Detectors? An Assessment Framework Using Evasive Soft Prompts. CoRR abs/2310.05095 (2023) - [i9]Suraj Jyothi Unni, Raha Moraffah, Huan Liu:
VQA-GEN: A Visual Question Answering Benchmark for Domain Generalization. CoRR abs/2311.00807 (2023) - 2022
- [j3]Lu Cheng, Ruocheng Guo, Raha Moraffah, Paras Sheth, K. Selçuk Candan, Huan Liu:
Evaluation Methods and Measures for Causal Learning Algorithms. IEEE Trans. Artif. Intell. 3(6): 924-943 (2022) - [c8]Raha Moraffah, Paras Sheth, Huan Liu:
Exploring the Target Distribution for Surrogate-Based Black-Box Attacks. IEEE Big Data 2022: 1310-1315 - [c7]Raha Moraffah, Huan Liu:
Query-Efficient Target-Agnostic Black-Box Attack. ICDM 2022: 368-377 - [i8]Lu Cheng, Ruocheng Guo, Raha Moraffah, Paras Sheth, K. Selçuk Candan, Huan Liu:
Evaluation Methods and Measures for Causal Learning Algorithms. CoRR abs/2202.02896 (2022) - [i7]Paras Sheth, Raha Moraffah, K. Selçuk Candan, Adrienne Raglin, Huan Liu:
Domain Generalization - A Causal Perspective. CoRR abs/2209.15177 (2022) - 2021
- [j2]Raha Moraffah, Paras Sheth, Mansooreh Karami, Anchit Bhattacharya, Qianru Wang, Anique Tahir, Adrienne Raglin, Huan Liu:
Causal inference for time series analysis: problems, methods and evaluation. Knowl. Inf. Syst. 63(12): 3041-3085 (2021) - [i6]Raha Moraffah, Paras Sheth, Mansooreh Karami, Anchit Bhattacharya, Qianru Wang, Anique Tahir, Adrienne Raglin, Huan Liu:
Causal Inference for Time series Analysis: Problems, Methods and Evaluation. CoRR abs/2102.05829 (2021) - 2020
- [j1]Raha Moraffah, Mansooreh Karami, Ruocheng Guo, Adrienne Raglin, Huan Liu:
Causal Interpretability for Machine Learning - Problems, Methods and Evaluation. SIGKDD Explor. 22(1): 18-33 (2020) - [c6]Bahman Moraffah, Christ Richmond, Raha Moraffah, Antonia Papandreou-Suppappola:
METRIC-Bayes: Measurements Estimation for Tracking in High Clutter using Bayesian Nonparametrics. ACSSC 2020: 1518-1522 - [c5]Adrienne Raglin, Raha Moraffah, Huan Liu:
Causality and Uncertainty of Information for Content Understanding. CogMI 2020: 109-113 - [i5]Raha Moraffah, Mansooreh Karami, Ruocheng Guo, Adrienne Raglin, Huan Liu:
Causal Interpretability for Machine Learning - Problems, Methods and Evaluation. CoRR abs/2003.03934 (2020) - [i4]Raha Moraffah, Bahman Moraffah, Mansooreh Karami, Adrienne Raglin, Huan Liu:
CAN: A Causal Adversarial Network for Learning Observational and Interventional Distributions. CoRR abs/2008.11376 (2020) - [i3]Bahman Moraffah, Christ Richmond, Raha Moraffah, Antonia Papandreou-Suppappola:
Use of Bayesian Nonparametric methods for Estimating the Measurements in High Clutter. CoRR abs/2012.09785 (2020)
2010 – 2019
- 2019
- [c4]Lu Cheng, Ruocheng Guo, Raha Moraffah, K. Selçuk Candan, Adrienne Raglin, Huan Liu:
A Practical Data Repository for Causal Learning with Big Data. Bench 2019: 234-248 - [i2]Raha Moraffah, Kai Shu, Adrienne Raglin, Huan Liu:
Deep causal representation learning for unsupervised domain adaptation. CoRR abs/1910.12417 (2019) - 2018
- [c3]Vineeth Rakesh, Ruocheng Guo, Raha Moraffah, Nitin Agarwal, Huan Liu:
Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects. CIKM 2018: 1679-1682 - [i1]Vineeth Rakesh, Ruocheng Guo, Raha Moraffah, Nitin Agarwal, Huan Liu:
Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects. CoRR abs/1808.03333 (2018) - 2017
- [c2]Mohamed Sarwat, Raha Moraffah, Mohamed F. Mokbel, James L. Avery:
Database System Support for Personalized Recommendation Applications. ICDE 2017: 1320-1331 - [c1]Jia Yu, Raha Moraffah, Mohamed Sarwat:
Hippo in Action: Scalable Indexing of a Billion New York City Taxi Trips and Beyond. ICDE 2017: 1413-1414
Coauthor Index
aka: Tharindu S. Kumarage
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