Saved in:
| Main Author: | Gray, Andy |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2603.17019 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
"They've Stolen My GPL-Licensed Model!": Toward Standardized and Transparent Model Licensing
by: Duan, Moming, et al.
Published: (2024)
by: Duan, Moming, et al.
Published: (2024)
Vision Transformers that Never Stop Learning
by: Sun, Caihao, et al.
Published: (2026)
by: Sun, Caihao, et al.
Published: (2026)
"I've Seen How This Goes": Characterizing Diversity via Progressive Conditional Surprise
by: Khoriaty, Matthew, et al.
Published: (2026)
by: Khoriaty, Matthew, et al.
Published: (2026)
Beyond the Seen: Bounded Distribution Estimation for Open-Vocabulary Learning
by: Fan, Xiaomeng, et al.
Published: (2025)
by: Fan, Xiaomeng, et al.
Published: (2025)
Escaping the SpuriVerse: Can Large Vision-Language Models Generalize Beyond Seen Spurious Correlations?
by: Yang, Yiwei, et al.
Published: (2025)
by: Yang, Yiwei, et al.
Published: (2025)
Bayesian Active Learning for Multi-Criteria Comparative Judgement in Educational Assessment
by: Gray, Andy, et al.
Published: (2025)
by: Gray, Andy, et al.
Published: (2025)
Malign Overfitting: Interpolation Can Provably Preclude Invariance
by: Wald, Yoav, et al.
Published: (2022)
by: Wald, Yoav, et al.
Published: (2022)
Seen-to-Scene: Keep the Seen, Generate the Unseen for Video Outpainting
by: Jeon, Inseok, et al.
Published: (2026)
by: Jeon, Inseok, et al.
Published: (2026)
Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models
by: Noorani, Sima, et al.
Published: (2025)
by: Noorani, Sima, et al.
Published: (2025)
Beyond Interpolation: Extrapolative Reasoning with Reinforcement Learning and Graph Neural Networks
by: Grillo, Niccolò, et al.
Published: (2025)
by: Grillo, Niccolò, et al.
Published: (2025)
Tabular Foundation Models Can Learn Association Rules
by: Karabulut, Erkan, et al.
Published: (2026)
by: Karabulut, Erkan, et al.
Published: (2026)
Beyond Benign Overfitting in Nadaraya-Watson Interpolators
by: Barzilai, Daniel, et al.
Published: (2025)
by: Barzilai, Daniel, et al.
Published: (2025)
Divide-Then-Rule: A Cluster-Driven Hierarchical Interpolator for Attribute-Missing Graphs
by: Hu, Yaowen, et al.
Published: (2025)
by: Hu, Yaowen, et al.
Published: (2025)
Beyond the Laplacian: Interpolated Spectral Augmentation for Graph Neural Networks
by: Cui, Ziyao, et al.
Published: (2025)
by: Cui, Ziyao, et al.
Published: (2025)
There Was Never a Bottleneck in Concept Bottleneck Models
by: Almudévar, Antonio, et al.
Published: (2025)
by: Almudévar, Antonio, et al.
Published: (2025)
The Greatest Films Never Seen
by: Op den Kamp, Claudy
Published: (2025)
by: Op den Kamp, Claudy
Published: (2025)
Transformers Learn Faster with Semantic Focus
by: Ram, Parikshit, et al.
Published: (2025)
by: Ram, Parikshit, et al.
Published: (2025)
Continual Learning with Weight Interpolation
by: Kozal, Jędrzej, et al.
Published: (2024)
by: Kozal, Jędrzej, et al.
Published: (2024)
AXELRAM: Quantize Once, Never Dequantize
by: Nishida, Yasushi
Published: (2026)
by: Nishida, Yasushi
Published: (2026)
Never Saddle for Reparameterized Steepest Descent as Mirror Flow
by: Jacobs, Tom, et al.
Published: (2026)
by: Jacobs, Tom, et al.
Published: (2026)
Functional Interpolation for Relative Positions Improves Long Context Transformers
by: Li, Shanda, et al.
Published: (2023)
by: Li, Shanda, et al.
Published: (2023)
Exact Sequence Interpolation with Transformers
by: Alcalde, Albert, et al.
Published: (2025)
by: Alcalde, Albert, et al.
Published: (2025)
Learning Straight Flows by Learning Curved Interpolants
by: Shankar, Shiv, et al.
Published: (2025)
by: Shankar, Shiv, et al.
Published: (2025)
Can Large Language Models Transform Computational Social Science?
by: Ziems, Caleb, et al.
Published: (2023)
by: Ziems, Caleb, et al.
Published: (2023)
Can LLMs Follow Simple Rules?
by: Mu, Norman, et al.
Published: (2023)
by: Mu, Norman, et al.
Published: (2023)
An Efficient Private GPT Never Autoregressively Decodes
by: Li, Zhengyi, et al.
Published: (2025)
by: Li, Zhengyi, et al.
Published: (2025)
Learning to Recall with Transformers Beyond Orthogonal Embeddings
by: Vural, Nuri Mert, et al.
Published: (2026)
by: Vural, Nuri Mert, et al.
Published: (2026)
Multitask Learning with Stochastic Interpolants
by: Negrel, Hugo, et al.
Published: (2025)
by: Negrel, Hugo, et al.
Published: (2025)
Can Transformers Learn Full Bayesian Inference in Context?
by: Reuter, Arik, et al.
Published: (2025)
by: Reuter, Arik, et al.
Published: (2025)
Beyond Perfect Scores: Proof-by-Contradiction for Trustworthy Machine Learning
by: Wadduwage, Dushan N., et al.
Published: (2026)
by: Wadduwage, Dushan N., et al.
Published: (2026)
A Smooth Sea Never Made a Skilled SAILOR: Robust Imitation via Learning to Search
by: Jain, Arnav Kumar, et al.
Published: (2025)
by: Jain, Arnav Kumar, et al.
Published: (2025)
Transformers Can Learn Temporal Difference Methods for In-Context Reinforcement Learning
by: Wang, Jiuqi, et al.
Published: (2024)
by: Wang, Jiuqi, et al.
Published: (2024)
The Bayesian Learning Rule
by: Khan, Mohammad Emtiyaz, et al.
Published: (2021)
by: Khan, Mohammad Emtiyaz, et al.
Published: (2021)
Compressing LLMs: The Truth is Rarely Pure and Never Simple
by: Jaiswal, Ajay, et al.
Published: (2023)
by: Jaiswal, Ajay, et al.
Published: (2023)
From Interpolation to Extrapolation: Complete Length Generalization for Arithmetic Transformers
by: Duan, Shaoxiong, et al.
Published: (2023)
by: Duan, Shaoxiong, et al.
Published: (2023)
The Problem of Plagiarism: Students Who Copy May Not Know They've Committed an Offense
by: MacDonell, Colleen
Published: (2005)
by: MacDonell, Colleen
Published: (2005)
Beyond Discriminant Patterns: On the Robustness of Decision Rule Ensembles
by: Du, Xin, et al.
Published: (2021)
by: Du, Xin, et al.
Published: (2021)
Unlabeled Data Can Provably Enhance In-Context Learning of Transformers
by: Liu, Renpu, et al.
Published: (2026)
by: Liu, Renpu, et al.
Published: (2026)
Can Transformers Break Encryption Schemes via In-Context Learning?
by: Korrapati, Jathin, et al.
Published: (2025)
by: Korrapati, Jathin, et al.
Published: (2025)
EditLord: Learning Code Transformation Rules for Code Editing
by: Li, Weichen, et al.
Published: (2025)
by: Li, Weichen, et al.
Published: (2025)
Similar Items
-
"They've Stolen My GPL-Licensed Model!": Toward Standardized and Transparent Model Licensing
by: Duan, Moming, et al.
Published: (2024) -
Vision Transformers that Never Stop Learning
by: Sun, Caihao, et al.
Published: (2026) -
"I've Seen How This Goes": Characterizing Diversity via Progressive Conditional Surprise
by: Khoriaty, Matthew, et al.
Published: (2026) -
Beyond the Seen: Bounded Distribution Estimation for Open-Vocabulary Learning
by: Fan, Xiaomeng, et al.
Published: (2025) -
Escaping the SpuriVerse: Can Large Vision-Language Models Generalize Beyond Seen Spurious Correlations?
by: Yang, Yiwei, et al.
Published: (2025)