conftrace_

out-of-distribution robustness

48 papers

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Also known as

OOD ROBUSTNESS

Co-occurring keywords

domain adaptation (4595) distribution shift (722) domain generalization (1522) contrastive learning (4032) representation learning (6206) spurious correlation (279) out-of-distribution generalization (408) data augmentation (3052) transfer learning (5449) model compression (3302)

Papers

Measuring Distribution Shift in User Prompts and Its Effects on LLM Performance ACL 2026
Generalizing Trust: Weak-to-Strong Trustworthiness in Language Models ACL 2026
Debiasing Logical Fallacy Detection for Real-World Robustness via Counterfactually Augmented Data ACL 2026
Domain Generalization using Large Pretrained Models with Mixture-of-Adapters WACV 2025
Scaling 3D Compositional Models for Robust Classification and Pose Estimation ICCV 2025
Information Density Principle for MLLM Benchmarks ICCV 2025
CNS-Bench: Benchmarking Image Classifier Robustness Under Continuous Nuisance Shifts ICCV 2025
CAT: Causal Attention Tuning For Injecting Fine-grained Causal Knowledge into Large Language Models EMNLP 2025
Benchmarking Object Detectors under Real-World Distribution Shifts in Satellite Imagery CVPR 2025
Demystifying optimized prompts in language models EMNLP 2025
Refining Latent Homophilic Structures over Heterophilic Graphs for Robust Graph Convolution Networks AAAI 2024
Robust Image Denoising through Adversarial Frequency Mixup CVPR 2024
A Bayesian Approach to OOD Robustness in Image Classification CVPR 2024
Bridging Distribution Gap via Semantic Rewriting with LLMs to Enhance OOD Robustness ACL 2024
Delving into Qualitative Implications of Synthetic Data for Hate Speech Detection EMNLP 2024
LoRASC: Expressive and Generalizable Low-rank Adaptation for Large Models via Slow Cascaded Learning EMNLP 2024
Domain Aligned CLIP for Few-Shot Classification WACV 2024
A theoretical design of concept sets: improving the predictability of concept bottleneck models NIPS 2024
Reconstruct and Match: Out-of-Distribution Robustness via Topological Homogeneity NIPS 2024
Towards Reliable Learning in the Wild: Generalization and Adaptation AAAI 2024
Robustness Challenges in Model Distillation and Pruning for Natural Language Understanding EACL 2023
There is more than one kind of robustness: Fooling Whisper with adversarial examples INTERSPEECH 2023
Probing Out-of-Distribution Robustness of Language Models with Parameter-Efficient Transfer Learning ACL 2023
Fast Trainable Projection for Robust Fine-tuning NIPS 2023
Effective Robustness against Natural Distribution Shifts for Models with Different Training Data NIPS 2023