out-of-distribution performance

Improving the OOD Performance of Closed-Source LLMs on NLI Through Strategic Data Selection EACL 2026 IT$^3$: Idempotent Test-Time Training ICML 2025 SOI Matters: Analyzing Multi-Setting Training Dynamics in Pretrained Language Models via Subsets of Interest EMNLP 2025 Tracr-Injection: Distilling Algorithms into Pre-trained Language Models ACL 2025 Monotonic Risk Relationships under Distribution Shifts for Regularized Risk Minimization JMLR 2024 Out of the Ordinary: Spectrally Adapting Regression for Covariate Shift ICML 2024 Predicting the Performance of Foundation Models via Agreement-on-the-Line NeurIPS 2024 Accuracy on the Curve: On the Nonlinear Correlation of ML Performance Between Data Subpopulations ICML 2023 Debiasing Multimodal Models via Causal Information Minimization EMNLP 2023 Using counterfactual contrast to improve compositional generalization for multi-step quantitative reasoning ACL 2023 Exploring The Landscape of Distributional Robustness for Question Answering Models EMNLP 2022 LILA: A Unified Benchmark for Mathematical Reasoning EMNLP 2022 Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time ICML 2022 When More Data Hurts: A Troubling Quirk in Developing Broad-Coverage Natural Language Understanding Systems EMNLP 2022 Noise or Signal: The Role of Image Backgrounds in Object Recognition ICLR 2021 Mind the Trade-off: Debiasing NLU Models without Degrading the In-distribution Performance ACL 2020