conftrace_

distribution shift

722 papers

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Also known as

DS

Co-occurring keywords

domain adaptation (4595) domain generalization (1522) out-of-distribution detection (617) test-time adaptation (312) out-of-distribution generalization (408) causal inference (1630) representation learning (6206) transfer learning (5449) covariate shift (157) graph neural network (3962)

Papers

Multilingual Diversity Improves Vision-Language Representations NIPS 2024
Distance-aware Calibration for Pre-trained Language Models EMNLP 2024
Efficient Test-Time Adaptation of Vision-Language Models CVPR 2024
REALM: Robust Entropy Adaptive Loss Minimization for Improved Single-Sample Test-Time Adaptation WACV 2024
Protected Test-Time Adaptation via Online Entropy Matching: A Betting Approach NIPS 2024
Beyond Document Page Classification: Design, Datasets, and Challenges WACV 2024
LatentDR: Improving Model Generalization Through Sample-Aware Latent Degradation and Restoration WACV 2024
Nearest Neighbor Sampling for Covariate Shift Adaptation JMLR 2024
Monotonic Risk Relationships under Distribution Shifts for Regularized Risk Minimization JMLR 2024
When do Generative Query and Document Expansions Fail? A Comprehensive Study Across Methods, Retrievers, and Datasets EACL 2024
RetroOOD: Understanding Out-of-Distribution Generalization in Retrosynthesis Prediction AAAI 2024
TinyTTA: Efficient Test-time Adaptation via Early-exit Ensembles on Edge Devices NIPS 2024
Bridging Multicalibration and Out-of-distribution Generalization Beyond Covariate Shift NIPS 2024
Learning to Reweight for Generalizable Graph Neural Network AAAI 2024
Examining the robustness of LLM evaluation to the distributional assumptions of benchmarks ACL 2024
Revisiting, Benchmarking and Understanding Unsupervised Graph Domain Adaptation NIPS 2024
Stochastic Optimization Schemes for Performative Prediction with Nonconvex Loss NIPS 2024
DADA: Distribution-Aware Domain Adaptation of PLMs for Information Retrieval ACL 2024
Class Distribution Shifts in Zero-Shot Learning: Learning Robust Representations NIPS 2024
Rethinking the Evaluation of Out-of-Distribution Detection: A Sorites Paradox NIPS 2024
De-confounded Data-free Knowledge Distillation for Handling Distribution Shifts CVPR 2024
Improving the Generalization of Segmentation Foundation Model under Distribution Shift via Weakly Supervised Adaptation CVPR 2024
On the Robustness of Language Guidance for Low-Level Vision Tasks: Findings from Depth Estimation CVPR 2024
Automatic De-Biased Temporal-Relational Modeling for Stock Investment Recommendation IJCAI 2024
Towards Robust Extractive Question Answering Models: Rethinking the Training Methodology EMNLP 2024