Watermarking Counterfactual Explanations
Fuente:
arXiv
Saved in:
| Main Authors: | Guo, Hangzhi, Choudhury, Firdaus Ahmed, Chen, Tinghua, Yadav, Amulya |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Designing User-Centric Metrics for Evaluation of Counterfactual Explanations
by: Choudhury, Firdaus Ahmed, et al.
Published: (2025)
by: Choudhury, Firdaus Ahmed, et al.
Published: (2025)
Debiasing Watermarks for Large Language Models via Maximal Coupling
by: Xie, Yangxinyu, et al.
Published: (2024)
by: Xie, Yangxinyu, et al.
Published: (2024)
Certified Causal Defense with Generalizable Robustness
by: Qiao, Yiran, et al.
Published: (2024)
by: Qiao, Yiran, et al.
Published: (2024)
Majority Vote for Distributed Differentially Private Sign Selection
by: Liu, Weidong, et al.
Published: (2022)
by: Liu, Weidong, et al.
Published: (2022)
Differentially Private Covariate Balancing Causal Inference
by: Ohnishi, Yuki, et al.
Published: (2024)
by: Ohnishi, Yuki, et al.
Published: (2024)
Differentially Private Range Queries with Correlated Input Perturbation
by: Dharangutte, Prathamesh, et al.
Published: (2024)
by: Dharangutte, Prathamesh, et al.
Published: (2024)
Testing Credibility of Public and Private Surveys through the Lens of Regression
by: Basu, Debabrota, et al.
Published: (2024)
by: Basu, Debabrota, et al.
Published: (2024)
Estimation of conditional average treatment effects on distributed confidential data
by: Kawamata, Yuji, et al.
Published: (2024)
by: Kawamata, Yuji, et al.
Published: (2024)
Privacy Preserving Adaptive Experiment Design
by: Li, Jiachun, et al.
Published: (2024)
by: Li, Jiachun, et al.
Published: (2024)
Resampling methods for private statistical inference
by: Chadha, Karan, et al.
Published: (2024)
by: Chadha, Karan, et al.
Published: (2024)
Improving the Variance of Differentially Private Randomized Experiments through Clustering
by: Javanmard, Adel, et al.
Published: (2023)
by: Javanmard, Adel, et al.
Published: (2023)
Differentially Private E-Values
by: Csillag, Daniel, et al.
Published: (2025)
by: Csillag, Daniel, et al.
Published: (2025)
CausalArmor: Efficient Indirect Prompt Injection Guardrails via Causal Attribution
by: Kim, Minbeom, et al.
Published: (2026)
by: Kim, Minbeom, et al.
Published: (2026)
Sequentially Auditing Differential Privacy
by: González, Tomás, et al.
Published: (2025)
by: González, Tomás, et al.
Published: (2025)
Auditing Differential Privacy in the Black-Box Setting
by: Shi, Kaining, et al.
Published: (2025)
by: Shi, Kaining, et al.
Published: (2025)
PrivATE: Differentially Private Confidence Intervals for Average Treatment Effects
by: Schröder, Maresa, et al.
Published: (2025)
by: Schröder, Maresa, et al.
Published: (2025)
PrAda-GAN: A Private Adaptive Generative Adversarial Network with Bayes Network Structure
by: Jia, Ke, et al.
Published: (2025)
by: Jia, Ke, et al.
Published: (2025)
Inference With Combining Rules From Multiple Differentially Private Synthetic Datasets
by: Nombo, Leila, et al.
Published: (2024)
by: Nombo, Leila, et al.
Published: (2024)
Privacy-Preserving Customer Support: A Framework for Secure and Scalable Interactions
by: Awasthi, Anant Prakash, et al.
Published: (2024)
by: Awasthi, Anant Prakash, et al.
Published: (2024)
Methods for generating and evaluating synthetic longitudinal patient data: a systematic review
by: Perkonoja, Katariina, et al.
Published: (2023)
by: Perkonoja, Katariina, et al.
Published: (2023)
Distortion-free Watermarks are not Truly Distortion-free under Watermark Key Collisions
by: Wu, Yihan, et al.
Published: (2024)
by: Wu, Yihan, et al.
Published: (2024)
De-amplifying Bias from Differential Privacy in Language Model Fine-tuning
by: Srivastava, Sanjari, et al.
Published: (2024)
by: Srivastava, Sanjari, et al.
Published: (2024)
Differentially Private Federated Learning: Servers Trustworthiness, Estimation, and Statistical Inference
by: Zhang, Zhe, et al.
Published: (2024)
by: Zhang, Zhe, et al.
Published: (2024)
Disentangle Estimation of Causal Effects from Cross-Silo Data
by: Liu, Yuxuan, et al.
Published: (2024)
by: Liu, Yuxuan, et al.
Published: (2024)
A Survey on Differential Privacy for SpatioTemporal Data in Transportation Research
by: Bhadani, Rahul
Published: (2024)
by: Bhadani, Rahul
Published: (2024)
Distribution-Aware Mean Estimation under User-level Local Differential Privacy
by: Pla, Corentin, et al.
Published: (2024)
by: Pla, Corentin, et al.
Published: (2024)
Federated Transfer Learning with Differential Privacy
by: Li, Mengchu, et al.
Published: (2024)
by: Li, Mengchu, et al.
Published: (2024)
CURATE: Scaling-up Differentially Private Causal Graph Discovery
by: Bhattacharjee, Payel, et al.
Published: (2024)
by: Bhattacharjee, Payel, et al.
Published: (2024)
Bayesian Adversarial Privacy
by: Bell, Cameron, et al.
Published: (2026)
by: Bell, Cameron, et al.
Published: (2026)
Nonparametric extensions of randomized response for private confidence sets
by: Waudby-Smith, Ian, et al.
Published: (2022)
by: Waudby-Smith, Ian, et al.
Published: (2022)
Towards Causal Deep Learning for Vulnerability Detection
by: Rahman, Md Mahbubur, et al.
Published: (2023)
by: Rahman, Md Mahbubur, et al.
Published: (2023)
Mitigating Privacy-Utility Trade-off in Decentralized Federated Learning via $f$-Differential Privacy
by: Li, Xiang, et al.
Published: (2025)
by: Li, Xiang, et al.
Published: (2025)
Causal Discovery Under Local Privacy
by: Binkytė, Rūta, et al.
Published: (2023)
by: Binkytė, Rūta, et al.
Published: (2023)
Score Attack: A Lower Bound Technique for Optimal Differentially Private Learning
by: Cai, T. Tony, et al.
Published: (2023)
by: Cai, T. Tony, et al.
Published: (2023)
Private Prediction Sets
by: Angelopoulos, Anastasios N., et al.
Published: (2021)
by: Angelopoulos, Anastasios N., et al.
Published: (2021)
Differentially Private Inference for Longitudinal Linear Regression
by: Sopa, Getoar, et al.
Published: (2026)
by: Sopa, Getoar, et al.
Published: (2026)
Differentially Private Permutation Tests: Applications to Kernel Methods
by: Kim, Ilmun, et al.
Published: (2023)
by: Kim, Ilmun, et al.
Published: (2023)
Explanation as a Watermark: Towards Harmless and Multi-bit Model Ownership Verification via Watermarking Feature Attribution
by: Shao, Shuo, et al.
Published: (2024)
by: Shao, Shuo, et al.
Published: (2024)
Watermarking Generative Categorical Data
by: Gu, Bochao, et al.
Published: (2024)
by: Gu, Bochao, et al.
Published: (2024)
Refined Detection for Gumbel Watermarking
by: Lattimore, Tor
Published: (2026)
by: Lattimore, Tor
Published: (2026)
Similar Items
-
Designing User-Centric Metrics for Evaluation of Counterfactual Explanations
by: Choudhury, Firdaus Ahmed, et al.
Published: (2025) -
Debiasing Watermarks for Large Language Models via Maximal Coupling
by: Xie, Yangxinyu, et al.
Published: (2024) -
Certified Causal Defense with Generalizable Robustness
by: Qiao, Yiran, et al.
Published: (2024) -
Majority Vote for Distributed Differentially Private Sign Selection
by: Liu, Weidong, et al.
Published: (2022) -
Differentially Private Covariate Balancing Causal Inference
by: Ohnishi, Yuki, et al.
Published: (2024)