Out-of-Distribution Detection Methods Answer the Wrong Questions
Fuente:
arXiv
Guardado en:
| Autores principales: | Li, Yucen Lily, Lu, Daohan, Kirichenko, Polina, Qiu, Shikai, Rudner, Tim G. J., Bruss, C. Bayan, Wilson, Andrew Gordon |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
A Study of Bayesian Neural Network Surrogates for Bayesian Optimization
por: Li, Yucen Lily, et al.
Publicado: (2023)
por: Li, Yucen Lily, et al.
Publicado: (2023)
Searching for Efficient Linear Layers over a Continuous Space of Structured Matrices
por: Potapczynski, Andres, et al.
Publicado: (2024)
por: Potapczynski, Andres, et al.
Publicado: (2024)
Visual Explanations of Image-Text Representations via Multi-Modal Information Bottleneck Attribution
por: Wang, Ying, et al.
Publicado: (2023)
por: Wang, Ying, et al.
Publicado: (2023)
Just How Flexible are Neural Networks in Practice?
por: Shwartz-Ziv, Ravid, et al.
Publicado: (2024)
por: Shwartz-Ziv, Ravid, et al.
Publicado: (2024)
Large Language Models Are Zero-Shot Time Series Forecasters
por: Gruver, Nate, et al.
Publicado: (2023)
por: Gruver, Nate, et al.
Publicado: (2023)
AI versus AI in Financial Crimes and Detection: GenAI Crime Waves to Co-Evolutionary AI
por: Kurshan, Eren, et al.
Publicado: (2024)
por: Kurshan, Eren, et al.
Publicado: (2024)
Mind the GAP: Improving Robustness to Subpopulation Shifts with Group-Aware Priors
por: Rudner, Tim G. J., et al.
Publicado: (2024)
por: Rudner, Tim G. J., et al.
Publicado: (2024)
Context-Guided Diffusion for Out-of-Distribution Molecular and Protein Design
por: Klarner, Leo, et al.
Publicado: (2024)
por: Klarner, Leo, et al.
Publicado: (2024)
Hyperparameter Transfer Enables Consistent Gains of Matrix-Preconditioned Optimizers Across Scales
por: Qiu, Shikai, et al.
Publicado: (2025)
por: Qiu, Shikai, et al.
Publicado: (2025)
Compute Better Spent: Replacing Dense Layers with Structured Matrices
por: Qiu, Shikai, et al.
Publicado: (2024)
por: Qiu, Shikai, et al.
Publicado: (2024)
Scaling Collapse Reveals Universal Dynamics in Compute-Optimally Trained Neural Networks
por: Qiu, Shikai, et al.
Publicado: (2025)
por: Qiu, Shikai, et al.
Publicado: (2025)
Understanding the Detrimental Class-level Effects of Data Augmentation
por: Kirichenko, Polina, et al.
Publicado: (2023)
por: Kirichenko, Polina, et al.
Publicado: (2023)
Non-Vacuous Generalization Bounds for Large Language Models
por: Lotfi, Sanae, et al.
Publicado: (2023)
por: Lotfi, Sanae, et al.
Publicado: (2023)
BEDTime: A Unified Benchmark for Automatically Describing Time Series
por: Sen, Medhasweta, et al.
Publicado: (2025)
por: Sen, Medhasweta, et al.
Publicado: (2025)
Transferring Knowledge from Large Foundation Models to Small Downstream Models
por: Qiu, Shikai, et al.
Publicado: (2024)
por: Qiu, Shikai, et al.
Publicado: (2024)
Modeling Caption Diversity in Contrastive Vision-Language Pretraining
por: Lavoie, Samuel, et al.
Publicado: (2024)
por: Lavoie, Samuel, et al.
Publicado: (2024)
Forgetting in Language Models: Capacity, Optimization, and Self-Generated Replay
por: Marek, Martin, et al.
Publicado: (2026)
por: Marek, Martin, et al.
Publicado: (2026)
Customizing the Inductive Biases of Softmax Attention using Structured Matrices
por: Kuang, Yilun, et al.
Publicado: (2025)
por: Kuang, Yilun, et al.
Publicado: (2025)
Is Sequence Information All You Need for Bayesian Optimization of Antibodies?
por: Ober, Sebastian W., et al.
Publicado: (2025)
por: Ober, Sebastian W., et al.
Publicado: (2025)
From Entropy to Epiplexity: Rethinking Information for Computationally Bounded Intelligence
por: Finzi, Marc, et al.
Publicado: (2026)
por: Finzi, Marc, et al.
Publicado: (2026)
Quantized Reasoning Models Think They Need to Think Longer, but They Do Not
por: Lotfi, Sanae, et al.
Publicado: (2026)
por: Lotfi, Sanae, et al.
Publicado: (2026)
Rethinking Out-of-Distribution Detection for Reinforcement Learning: Advancing Methods for Evaluation and Detection
por: Nasvytis, Linas, et al.
Publicado: (2024)
por: Nasvytis, Linas, et al.
Publicado: (2024)
A Unification of Discrete, Gaussian, and Simplicial Diffusion
por: Chandra, Nuria Alina, et al.
Publicado: (2025)
por: Chandra, Nuria Alina, et al.
Publicado: (2025)
Improving Semantic Uncertainty Quantification in Language Model Question-Answering via Token-Level Temperature Scaling
por: Lamb, Tom A., et al.
Publicado: (2026)
por: Lamb, Tom A., et al.
Publicado: (2026)
When Answers Stray from Questions: Hallucination Detection via Question-Answer Orthogonal Decomposition
por: Yao, Siyang, et al.
Publicado: (2026)
por: Yao, Siyang, et al.
Publicado: (2026)
Zero-shot Multivariate Time Series Forecasting Using Tabular Prior Fitted Networks
por: Jayawardhana, Mayuka, et al.
Publicado: (2026)
por: Jayawardhana, Mayuka, et al.
Publicado: (2026)
Integrating Sequential and Relational Modeling for User Events: Datasets and Prediction Tasks
por: Fathony, Rizal, et al.
Publicado: (2025)
por: Fathony, Rizal, et al.
Publicado: (2025)
Controllable Prompt Tuning For Balancing Group Distributional Robustness
por: Phan, Hoang, et al.
Publicado: (2024)
por: Phan, Hoang, et al.
Publicado: (2024)
Deep Learning is Not So Mysterious or Different
por: Wilson, Andrew Gordon
Publicado: (2025)
por: Wilson, Andrew Gordon
Publicado: (2025)
Embedding Trust: Semantic Isotropy Predicts Nonfactuality in Long-Form Text Generation
por: Bhardwaj, Dhrupad, et al.
Publicado: (2025)
por: Bhardwaj, Dhrupad, et al.
Publicado: (2025)
What's in Common? Multimodal Models Hallucinate When Reasoning Across Scenes
por: Ross, Candace, et al.
Publicado: (2025)
por: Ross, Candace, et al.
Publicado: (2025)
The Impact of Coreset Selection on Spurious Correlations and Group Robustness
por: Dharmasiri, Amaya, et al.
Publicado: (2025)
por: Dharmasiri, Amaya, et al.
Publicado: (2025)
AbstentionBench: Reasoning LLMs Fail on Unanswerable Questions
por: Kirichenko, Polina, et al.
Publicado: (2025)
por: Kirichenko, Polina, et al.
Publicado: (2025)
Can Transformers Learn Full Bayesian Inference in Context?
por: Reuter, Arik, et al.
Publicado: (2025)
por: Reuter, Arik, et al.
Publicado: (2025)
LLM Knowledge is Brittle: Truthfulness Representations Rely on Superficial Resemblance
por: Haller, Patrick, et al.
Publicado: (2025)
por: Haller, Patrick, et al.
Publicado: (2025)
GOLD: Graph Out-of-Distribution Detection via Implicit Adversarial Latent Generation
por: Wang, Danny, et al.
Publicado: (2025)
por: Wang, Danny, et al.
Publicado: (2025)
Varying Shades of Wrong: Aligning LLMs with Wrong Answers Only
por: Yao, Jihan, et al.
Publicado: (2024)
por: Yao, Jihan, et al.
Publicado: (2024)
Towards Optimal Feature-Shaping Methods for Out-of-Distribution Detection
por: Zhao, Qinyu, et al.
Publicado: (2024)
por: Zhao, Qinyu, et al.
Publicado: (2024)
What Information Matters? Graph Out-of-Distribution Detection via Tri-Component Information Decomposition
por: Wang, Danny, et al.
Publicado: (2026)
por: Wang, Danny, et al.
Publicado: (2026)
Data-Driven Priors for Uncertainty-Aware Deterioration Risk Prediction with Multimodal Data
por: López, L. Julián Lechuga, et al.
Publicado: (2026)
por: López, L. Julián Lechuga, et al.
Publicado: (2026)
Ejemplares similares
-
A Study of Bayesian Neural Network Surrogates for Bayesian Optimization
por: Li, Yucen Lily, et al.
Publicado: (2023) -
Searching for Efficient Linear Layers over a Continuous Space of Structured Matrices
por: Potapczynski, Andres, et al.
Publicado: (2024) -
Visual Explanations of Image-Text Representations via Multi-Modal Information Bottleneck Attribution
por: Wang, Ying, et al.
Publicado: (2023) -
Just How Flexible are Neural Networks in Practice?
por: Shwartz-Ziv, Ravid, et al.
Publicado: (2024) -
Large Language Models Are Zero-Shot Time Series Forecasters
por: Gruver, Nate, et al.
Publicado: (2023)