{"total":188,"rows":[{"id":"2103.03097","title":"Generalizing to Unseen Domains: A Survey on Domain Generalization","created":"2021-03-02","cited_by_count":766,"area":null},{"id":"2108.13624","title":"Towards Out-Of-Distribution Generalization: A Survey","created":"2021-08-31","cited_by_count":436,"area":null},{"id":"2102.09548","title":"Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development","created":"2021-02-18","cited_by_count":264,"area":null},{"id":"2106.06607","title":"Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization","created":"2021-06-11","cited_by_count":220,"area":null},{"id":"2203.01517","title":"Correct-N-Contrast: A Contrastive Approach for Improving Robustness to Spurious Correlations","created":"2022-03-03","cited_by_count":172,"area":null},{"id":"2202.02466","title":"Handling Distribution Shifts on Graphs: An Invariance Perspective","created":"2022-02-05","cited_by_count":164,"area":null},{"id":"2101.01134","title":"Does Invariant Risk Minimization Capture Invariance?","created":"2021-01-04","cited_by_count":116,"area":null},{"id":"2102.11436","title":"Model-Based Domain Generalization","created":"2021-02-23","cited_by_count":104,"area":null},{"id":"2106.04496","title":"Towards a Theoretical Framework of Out-of-Distribution Generalization","created":"2021-06-08","cited_by_count":94,"area":null},{"id":"2111.13839","title":"Towards Principled Disentanglement for Domain Generalization","created":"2021-11-27","cited_by_count":91,"area":null},{"id":"2106.03721","title":"OoD-Bench: Quantifying and Understanding Two Dimensions of Out-of-Distribution Generalization","created":"2021-06-07","cited_by_count":86,"area":null},{"id":"2108.08782","title":"Causal Attention for Unbiased Visual Recognition","created":"2021-08-19","cited_by_count":80,"area":null},{"id":"2106.02890","title":"Can Subnetwork Structure be the Key to Out-of-Distribution Generalization?","created":"2021-06-05","cited_by_count":75,"area":null},{"id":"2106.12674","title":"Fairness via Representation Neutralization","created":"2021-06-23","cited_by_count":63,"area":null},{"id":"2203.05818","title":"ZIN: When and How to Learn Invariance Without Environment Partition?","created":"2022-03-11","cited_by_count":58,"area":null},{"id":"2306.09158","title":"Feed Two Birds with One Scone: Exploiting Wild Data for Both Out-of-Distribution Generalization and Detection","created":"2023-06-15","cited_by_count":57,"area":null},{"id":"2102.11203","title":"A Theory of Label Propagation for Subpopulation Shift","created":"2021-02-22","cited_by_count":48,"area":null},{"id":"2203.11528","title":"Out-of-distribution Generalization with Causal Invariant Transformations","created":"2022-03-22","cited_by_count":45,"area":null},{"id":"2211.14666","title":"Synergies between Disentanglement and Sparsity: Generalization and Identifiability in Multi-Task Learning","created":"2022-11-26","cited_by_count":44,"area":null},{"id":"2301.09819","title":"Model Agnostic Sample Reweighting for Out-of-Distribution Learning","created":"2023-01-24","cited_by_count":44,"area":null},{"id":"2102.12353","title":"Nonlinear Invariant Risk Minimization: A Causal Approach","created":"2021-02-24","cited_by_count":42,"area":null},{"id":"2308.00788","title":"An Introduction to Bi-level Optimization: Foundations and Applications in Signal Processing and Machine Learning","created":"2023-08-01","cited_by_count":41,"area":null},{"id":"2111.14820","title":"Towards Robust and Adaptive Motion Forecasting: A Causal Representation Perspective","created":"2021-11-29","cited_by_count":40,"area":null},{"id":"2104.01678","title":"Understanding Continual Learning Settings with Data Distribution Drift Analysis","created":"2021-04-04","cited_by_count":38,"area":null},{"id":"2211.02843","title":"Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift","created":"2022-11-05","cited_by_count":38,"area":null},{"id":"2106.03632","title":"Quantifying and Improving Transferability in Domain Generalization","created":"2021-06-07","cited_by_count":35,"area":null},{"id":"2103.11163","title":"An Empirical Framework for Domain Generalization in Clinical Settings","created":"2021-03-20","cited_by_count":32,"area":null},{"id":"2201.12919","title":"Provable Domain Generalization via Invariant-Feature Subspace Recovery","created":"2022-01-30","cited_by_count":32,"area":null},{"id":"2304.07939","title":"Leveraging sparse and shared feature activations for disentangled representation learning","created":"2023-04-17","cited_by_count":32,"area":null},{"id":"2202.05436","title":"Minimax Regret Optimization for Robust Machine Learning under Distribution Shift","created":"2022-02-11","cited_by_count":31,"area":null},{"id":"2203.09978","title":"WOODS: Benchmarks for Out-of-Distribution Generalization in Time Series","created":"2022-03-18","cited_by_count":30,"area":null},{"id":"2107.02629","title":"Embracing the Dark Knowledge: Domain Generalization Using Regularized Knowledge Distillation","created":"2021-07-06","cited_by_count":29,"area":"distill"},{"id":"2109.02038","title":"NAS-OoD: Neural Architecture Search for Out-of-Distribution Generalization","created":"2021-09-05","cited_by_count":28,"area":null},{"id":"2205.09797","title":"Improving Multi-Task Generalization via Regularizing Spurious Correlation","created":"2022-05-19","cited_by_count":28,"area":null},{"id":"2101.07732","title":"Out-of-distribution Prediction with Invariant Risk Minimization: The Limitation and An Effective Fix","created":"2021-01-16","cited_by_count":27,"area":null},{"id":"2311.11114","title":"Environment-Aware Dynamic Graph Learning for Out-of-Distribution Generalization","created":"2023-11-18","cited_by_count":26,"area":null},{"id":"2103.15890","title":"Learning Domain Invariant Representations for Generalizable Person Re-Identification","created":"2021-03-29","cited_by_count":22,"area":null},{"id":"2201.11986","title":"Gradient Masked Averaging for Federated Learning","created":"2022-01-28","cited_by_count":22,"area":null},{"id":"2309.12559","title":"Invariant Learning via Probability of Sufficient and Necessary Causes","created":"2023-09-22","cited_by_count":22,"area":null},{"id":"2506.01339","title":"Invariance Makes LLM Unlearning Resilient Even to Unanticipated Downstream Fine-Tuning","created":"2025-06-02","cited_by_count":21,"area":"safety"},{"id":"2106.00925","title":"Contrastive ACE: Domain Generalization Through Alignment of Causal Mechanisms","created":"2021-06-02","cited_by_count":20,"area":null},{"id":"2210.07571","title":"Mix and Reason: Reasoning over Semantic Topology with Data Mixing for Domain Generalization","created":"2022-10-14","cited_by_count":20,"area":null},{"id":"2303.03052","title":"Masked Images Are Counterfactual Samples for Robust Fine-tuning","created":"2023-03-06","cited_by_count":20,"area":null},{"id":"2403.20233","title":"Functional Bilevel Optimization for Machine Learning","created":"2024-03-29","cited_by_count":20,"area":null},{"id":"2403.05026","title":"Spectral Invariant Learning for Dynamic Graphs under Distribution Shifts","created":"2024-03-08","cited_by_count":19,"area":null},{"id":"2109.05826","title":"Variational Disentanglement for Domain Generalization","created":"2021-09-13","cited_by_count":18,"area":null},{"id":"2202.12570","title":"Multi-Instance Causal Representation Learning for Instance Label Prediction and Out-of-Distribution Generalization","created":"2022-02-25","cited_by_count":17,"area":null},{"id":"2410.19265","title":"A Survey of Deep Graph Learning under Distribution Shifts: from Graph Out-of-Distribution Generalization to Adaptation","created":"2024-10-25","cited_by_count":17,"area":null},{"id":"2105.12628","title":"Predict then Interpolate: A Simple Algorithm to Learn Stable Classifiers","created":"2021-05-26","cited_by_count":16,"area":null},{"id":"2109.11990","title":"Optimization-based Causal Estimation from Heterogenous Environments","created":"2021-09-24","cited_by_count":16,"area":null},{"id":"2309.08825","title":"Distributionally Robust Post-hoc Classifiers under Prior Shifts","created":"2023-09-16","cited_by_count":16,"area":null},{"id":"2107.00778","title":"On Bridging Generic and Personalized Federated Learning for Image Classification","created":"2021-07-02","cited_by_count":15,"area":null},{"id":"2110.08413","title":"Invariant Language Modeling","created":"2021-10-16","cited_by_count":15,"area":null},{"id":"2203.15566","title":"Core Risk Minimization using Salient ImageNet","created":"2022-03-28","cited_by_count":15,"area":null},{"id":"2206.10816","title":"Fighting Fire with Fire: Avoiding DNN Shortcuts through Priming","created":"2022-06-22","cited_by_count":15,"area":null},{"id":"2311.01489","title":"Invariant Causal Imitation Learning for Generalizable Policies","created":"2023-11-02","cited_by_count":15,"area":"offlinerl"},{"id":"2207.12258","title":"Equivariance and Invariance Inductive Bias for Learning from Insufficient Data","created":"2022-07-25","cited_by_count":14,"area":null},{"id":"2208.10156","title":"Meta-Causal Feature Learning for Out-of-Distribution Generalization","created":"2022-08-22","cited_by_count":14,"area":null},{"id":"2209.15177","title":"Domain Generalization -- A Causal Perspective","created":"2022-09-30","cited_by_count":14,"area":null},{"id":"2211.00184","title":"FL Games: A Federated Learning Framework for Distribution Shifts","created":"2022-10-31","cited_by_count":14,"area":null},{"id":"2302.06975","title":"A Review of the Role of Causality in Developing Trustworthy AI Systems","created":"2023-02-14","cited_by_count":14,"area":null},{"id":"2309.07438","title":"Towards Artificial General Intelligence (AGI) in the Internet of Things (IoT): Opportunities and Challenges","created":"2023-09-14","cited_by_count":14,"area":null},{"id":"2407.11083","title":"Empowering Graph Invariance Learning with Deep Spurious Infomax","created":"2024-07-13","cited_by_count":14,"area":null},{"id":"2410.11397","title":"FOOGD: Federated Collaboration for Both Out-of-distribution Generalization and Detection","created":"2024-10-15","cited_by_count":14,"area":null},{"id":"2307.08232","title":"Learning for Counterfactual Fairness from Observational Data","created":"2023-07-17","cited_by_count":13,"area":null},{"id":"2402.07785","title":"HYPO: Hyperspherical Out-of-Distribution Generalization","created":"2024-02-12","cited_by_count":13,"area":null},{"id":"2106.12124","title":"Secure Domain Adaptation with Multiple Sources","created":"2021-06-23","cited_by_count":12,"area":null},{"id":"2210.09236","title":"ZooD: Exploiting Model Zoo for Out-of-Distribution Generalization","created":"2022-10-17","cited_by_count":12,"area":null},{"id":"2101.08521","title":"Out-of-Distribution Generalization Analysis via Influence Function","created":"2021-01-21","cited_by_count":11,"area":null},{"id":"2205.12753","title":"An Empirical Study on Distribution Shift Robustness From the Perspective of Pre-Training and Data Augmentation","created":"2022-05-25","cited_by_count":11,"area":null},{"id":"2206.14917","title":"Towards out of distribution generalization for problems in mechanics","created":"2022-06-29","cited_by_count":11,"area":null},{"id":"2405.11034","title":"Safety in Graph Machine Learning: Threats and Safeguards","created":"2024-05-17","cited_by_count":11,"area":null},{"id":"2106.09777","title":"On Invariance Penalties for Risk Minimization","created":"2021-06-17","cited_by_count":10,"area":null},{"id":"2109.01668","title":"How Reliable Are Out-of-Distribution Generalization Methods for Medical Image Segmentation?","created":"2021-09-03","cited_by_count":10,"area":null},{"id":"2303.02343","title":"What Is Missing in IRM Training and Evaluation? Challenges and Solutions","created":"2023-03-04","cited_by_count":10,"area":null},{"id":"2311.14315","title":"Robust Domain Misinformation Detection via Multi-modal Feature Alignment","created":"2023-11-24","cited_by_count":10,"area":null},{"id":"2211.01914","title":"FedGen: Generalizable Federated Learning for Sequential Data","created":"2022-11-03","cited_by_count":9,"area":null},{"id":"2310.04724","title":"Activate and Reject: Towards Safe Domain Generalization under Category Shift","created":"2023-10-07","cited_by_count":9,"area":null},{"id":"2406.13544","title":"One Fits All: Learning Fair Graph Neural Networks for Various Sensitive Attributes","created":"2024-06-19","cited_by_count":9,"area":null},{"id":"2305.01134","title":"PGrad: Learning Principal Gradients For Domain Generalization","created":"2023-05-02","cited_by_count":8,"area":null},{"id":"2103.12947","title":"Meta-Learned Invariant Risk Minimization","created":"2021-03-24","cited_by_count":7,"area":null},{"id":"2403.17592","title":"On the Benefits of Over-parameterization for Out-of-Distribution Generalization","created":"2024-03-26","cited_by_count":7,"area":null},{"id":"2410.08000","title":"AHA: Human-Assisted Out-of-Distribution Generalization and Detection","created":"2024-10-10","cited_by_count":7,"area":null},{"id":"2106.07847","title":"Learning Stable Classifiers by Transferring Unstable Features","created":"2021-06-15","cited_by_count":6,"area":null},{"id":"2209.07682","title":"Masked Imitation Learning: Discovering Environment-Invariant Modalities in Multimodal Demonstrations","created":"2022-09-16","cited_by_count":6,"area":"offlinerl"},{"id":"2210.10010","title":"Vision Paper: Causal Inference for Interpretable and Robust Machine Learning in Mobility Analysis","created":"2022-10-18","cited_by_count":6,"area":null},{"id":"2211.15724","title":"Malign Overfitting: Interpolation Can Provably Preclude Invariance","created":"2022-11-28","cited_by_count":6,"area":null},{"id":"2310.05348","title":"Continuous Invariance Learning","created":"2023-10-09","cited_by_count":6,"area":null},{"id":"2403.19863","title":"DeNetDM: Debiasing by Network Depth Modulation","created":"2024-03-28","cited_by_count":6,"area":null},{"id":"2408.07772","title":"Out-of-Distribution Learning with Human Feedback","created":"2024-08-14","cited_by_count":6,"area":"alignment"},{"id":"2107.01791","title":"Doing Good or Doing Right? Exploring the Weakness of Commonsense Causal Reasoning Models","created":"2021-07-05","cited_by_count":5,"area":null},{"id":"2208.06987","title":"The Causal Structure of Domain Invariant Supervised Representation Learning","created":"2022-08-15","cited_by_count":5,"area":null},{"id":"2210.03150","title":"Towards Out-of-Distribution Adversarial Robustness","created":"2022-10-06","cited_by_count":5,"area":null},{"id":"2212.09082","title":"On the Connection between Invariant Learning and Adversarial Training for Out-of-Distribution Generalization","created":"2022-12-18","cited_by_count":5,"area":null},{"id":"2301.12067","title":"Learning Optimal Features via Partial Invariance","created":"2023-01-28","cited_by_count":5,"area":null},{"id":"2311.15545","title":"Out-of-Distribution Generalized Dynamic Graph Neural Network for Human Albumin Prediction","created":"2023-11-27","cited_by_count":5,"area":null},{"id":"2407.14058","title":"Towards the Causal Complete Cause of Multi-Modal Representation Learning","created":"2024-07-19","cited_by_count":5,"area":null},{"id":"2411.12201","title":"Invariant Shape Representation Learning For Image Classification","created":"2024-11-19","cited_by_count":5,"area":null},{"id":"2506.17718","title":"Learning Time-Aware Causal Representation for Model Generalization in Evolving Domains","created":"2025-06-21","cited_by_count":5,"area":null},{"id":"2106.13899","title":"Domain Conditional Predictors for Domain Adaptation","created":"2021-06-25","cited_by_count":4,"area":null}],"next_cursor":"100"}