| Causal interpretability for machine learning-problems, methods and evaluation R Moraffah, M Karami, R Guo, A Raglin, H Liu ACM SIGKDD Explorations Newsletter 22 (1), 18-33, 2020 | 346 | 2020 |
| Causal inference for time series analysis: Problems, methods and evaluation R Moraffah, P Sheth, M Karami, A Bhattacharya, Q Wang, A Tahir, ... Knowledge and Information Systems 63 (12), 3041-3085, 2021 | 199 | 2021 |
| Evaluation methods and measures for causal learning algorithms L Cheng, R Guo, R Moraffah, P Sheth, KS Candan, H Liu IEEE Transactions on Artificial Intelligence 3 (6), 924-943, 2022 | 117 | 2022 |
| Conda: Contrastive domain adaptation for ai-generated text detection A Bhattacharjee, T Kumarage, R Moraffah, H Liu arXiv preprint arXiv:2309.03992, 2023 | 88 | 2023 |
| Towards llm-guided causal explainability for black-box text classifiers A Bhattacharjee, R Moraffah, J Garland, H Liu arXiv preprint arXiv:2309.13340, 2023 | 62 | 2023 |
| Linked causal variational autoencoder for inferring paired spillover effects V Rakesh, R Guo, R Moraffah, N Agarwal, H Liu Proceedings of the 27th ACM International Conference on Information and …, 2018 | 44 | 2018 |
| Domain Generalization--A Causal Perspective P Sheth, R Moraffah, KS Candan, A Raglin, H Liu arXiv preprint arXiv:2209.15177, 2022 | 35 | 2022 |
| How reliable are ai-generated-text detectors? an assessment framework using evasive soft prompts T Kumarage, P Sheth, R Moraffah, J Garland, H Liu arXiv preprint arXiv:2310.05095, 2023 | 31 | 2023 |
| The wolf within: Covert injection of malice into mllm societies via an mllm operative Z Tan, C Zhao, R Moraffah, Y Li, Y Kong, T Chen, H Liu arXiv preprint arXiv:2402.14859, 2024 | 30 | 2024 |
| " Glue pizza and eat rocks"--Exploiting Vulnerabilities in Retrieval-Augmented Generative Models Z Tan, C Zhao, R Moraffah, Y Li, S Wang, J Li, T Chen, H Liu arXiv preprint arXiv:2406.19417, 2024 | 27 | 2024 |
| A survey of ai-generated text forensic systems: Detection, attribution, and characterization T Kumarage, G Agrawal, P Sheth, R Moraffah, A Chadha, J Garland, H Liu arXiv preprint arXiv:2403.01152, 2024 | 27 | 2024 |
| Database system support for personalized recommendation applications M Sarwat, R Moraffah, MF Mokbel, JL Avery 2017 IEEE 33rd International Conference on Data Engineering (ICDE), 1320-1331, 2017 | 24 | 2017 |
| Causal adversarial network for learning conditional and interventional distributions R Moraffah, B Moraffah, M Karami, A Raglin, H Liu arXiv preprint arXiv:2008.11376, 2020 | 22 | 2020 |
| Llms as counterfactual explanation modules: Can chatgpt explain black-box text classifiers A Bhattacharjee, R Moraffah, J Garland, H Liu arXiv preprint arXiv:2309.13340 4, 2023 | 21 | 2023 |
| Eagle: A domain generalization framework for ai-generated text detection A Bhattacharjee, R Moraffah, J Garland, H Liu arXiv preprint arXiv:2403.15690, 2024 | 20 | 2024 |
| Zero-shot LLM-guided counterfactual generation: A case study on NLP model evaluation A Bhattacharjee, R Moraffah, J Garland, H Liu 2024 IEEE International Conference on Big Data (BigData), 1243-1248, 2024 | 17 | 2024 |
| Causality guided disentanglement for cross-platform hate speech detection P Sheth, R Moraffah, TS Kumarage, A Chadha, H Liu Proceedings of the 17th ACM international conference on web search and data …, 2024 | 16 | 2024 |
| Peace: Cross-platform hate speech detection-a causality-guided framework P Sheth, T Kumarage, R Moraffah, A Chadha, H Liu Joint european conference on machine learning and knowledge discovery in …, 2023 | 16 | 2023 |
| Deep causal representation learning for unsupervised domain adaptation R Moraffah, K Shu, A Raglin, H Liu arXiv preprint arXiv:1910.12417, 2019 | 16 | 2019 |
| Adversarial text purification: A large language model approach for defense R Moraffah, S Khandelwal, A Bhattacharjee, H Liu Pacific-Asia Conference on Knowledge Discovery and Data Mining, 65-77, 2024 | 14 | 2024 |
Huan LiuRegents Professor, Arizona State UniversityVerified email at asu.edu
