Saved in:
| Main Authors: | Cook, Dave, Klawa, Tim |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2505.14964 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Exposing the Achilles' Heel: Evaluating LLMs Ability to Handle Mistakes in Mathematical Reasoning
by: Singh, Joykirat, et al.
Published: (2024)
by: Singh, Joykirat, et al.
Published: (2024)
Achilles' Heels: Vulnerable Record Identification in Synthetic Data Publishing
by: Meeus, Matthieu, et al.
Published: (2023)
by: Meeus, Matthieu, et al.
Published: (2023)
Generative AI Training and Copyright Law
by: Stober, Sebastian, et al.
Published: (2025)
by: Stober, Sebastian, et al.
Published: (2025)
Enhancing Smart Farming Through Federated Learning: A Secure, Scalable, and Efficient Approach for AI-Driven Agriculture
by: Janga, Ritesh, et al.
Published: (2025)
by: Janga, Ritesh, et al.
Published: (2025)
Scaling Laws for Pre-training Agents and World Models
by: Pearce, Tim, et al.
Published: (2024)
by: Pearce, Tim, et al.
Published: (2024)
Spurious Correlation Learning in Preference Optimization: Mechanisms, Consequences, and Mitigation via Tie Training
by: Moya, Christian, et al.
Published: (2026)
by: Moya, Christian, et al.
Published: (2026)
Cyborg Data: Merging Human with AI Generated Training Data
by: North, Kai, et al.
Published: (2025)
by: North, Kai, et al.
Published: (2025)
Data Warmup: Complexity-Aware Curricula for Efficient Diffusion Training
by: Lin, Jinhong, et al.
Published: (2026)
by: Lin, Jinhong, et al.
Published: (2026)
Multimodal Visual-Tactile Representation Learning through Self-Supervised Contrastive Pre-Training
by: Dave, Vedant, et al.
Published: (2024)
by: Dave, Vedant, et al.
Published: (2024)
Fundamental Limits of Deep Learning-Based Binary Classifiers Trained with Hinge Loss
by: Getu, Tilahun M., et al.
Published: (2023)
by: Getu, Tilahun M., et al.
Published: (2023)
Uncovering Gradient Inversion Risks in Practical Language Model Training
by: Feng, Xinguo, et al.
Published: (2025)
by: Feng, Xinguo, et al.
Published: (2025)
Achilles' Heel of Mamba: Essential difficulties of the Mamba architecture demonstrated by synthetic data
by: Chen, Tianyi, et al.
Published: (2025)
by: Chen, Tianyi, et al.
Published: (2025)
AI-CARE: Carbon-Aware Reporting Evaluation Metric for AI Models
by: Santosh, KC, et al.
Published: (2026)
by: Santosh, KC, et al.
Published: (2026)
Noise-Aware Training of Layout-Aware Language Models
by: Sarkhel, Ritesh, et al.
Published: (2024)
by: Sarkhel, Ritesh, et al.
Published: (2024)
Conflict-Aware Adversarial Training
by: Xue, Zhiyu, et al.
Published: (2024)
by: Xue, Zhiyu, et al.
Published: (2024)
QuAIL: Quality-Aware Inertial Learning for Robust Training under Data Corruption
by: Sabella, Mattia, et al.
Published: (2026)
by: Sabella, Mattia, et al.
Published: (2026)
Utility-Aware Data Pricing: Token-Level Quality and Empirical Training Gain for LLMs
by: Xu, Minghui, et al.
Published: (2026)
by: Xu, Minghui, et al.
Published: (2026)
A Note on Shumailov et al. (2024): `AI Models Collapse When Trained on Recursively Generated Data'
by: Borji, Ali
Published: (2024)
by: Borji, Ali
Published: (2024)
Diffusion-Modeled Reinforcement Learning for Carbon and Risk-Aware Microgrid Optimization
by: Zhao, Yunyi, et al.
Published: (2025)
by: Zhao, Yunyi, et al.
Published: (2025)
Model-Based Epistemic Variance of Values for Risk-Aware Policy Optimization
by: Luis, Carlos E., et al.
Published: (2023)
by: Luis, Carlos E., et al.
Published: (2023)
Fast-DataShapley: Neural Modeling for Training Data Valuation
by: Sun, Haifeng, et al.
Published: (2025)
by: Sun, Haifeng, et al.
Published: (2025)
The Achilles' Heel of LLMs: How Altering a Handful of Neurons Can Cripple Language Abilities
by: Qin, Zixuan, et al.
Published: (2025)
by: Qin, Zixuan, et al.
Published: (2025)
OAT-Rephrase: Optimization-Aware Training Data Rephrasing for Zeroth-Order LLM Fine-Tuning
by: Long, Jikai, et al.
Published: (2025)
by: Long, Jikai, et al.
Published: (2025)
Hephaestus: Improving Fundamental Agent Capabilities of Large Language Models through Continual Pre-Training
by: Zhuang, Yuchen, et al.
Published: (2025)
by: Zhuang, Yuchen, et al.
Published: (2025)
Compute-Optimal Quantization-Aware Training
by: Dremov, Aleksandr, et al.
Published: (2025)
by: Dremov, Aleksandr, et al.
Published: (2025)
Load-Aware Training Scheduling for Model Circulation-based Decentralized Federated Learning
by: Kainuma, Haruki, et al.
Published: (2025)
by: Kainuma, Haruki, et al.
Published: (2025)
Certified Policy Optimisation for Nested Causal Bandits via PAC-Bayes Risk
by: Woydt, Tim, et al.
Published: (2026)
by: Woydt, Tim, et al.
Published: (2026)
Provable Training Data Identification for Large Language Models
by: Liu, Zhenlong, et al.
Published: (2025)
by: Liu, Zhenlong, et al.
Published: (2025)
Identifying the Achilles' Heel: An Iterative Method for Dynamically Uncovering Factual Errors in Large Language Models
by: Wang, Wenxuan, et al.
Published: (2024)
by: Wang, Wenxuan, et al.
Published: (2024)
Membership Privacy Risks of Sharpness Aware Minimization
by: Kim, Young In, et al.
Published: (2023)
by: Kim, Young In, et al.
Published: (2023)
The Strain of Success: A Predictive Model for Injury Risk Mitigation and Team Success in Soccer
by: Everett, Gregory, et al.
Published: (2024)
by: Everett, Gregory, et al.
Published: (2024)
Improved Sample Complexity For Diffusion Model Training Without Empirical Risk Minimizer Access
by: Gaur, Mudit, et al.
Published: (2025)
by: Gaur, Mudit, et al.
Published: (2025)
Symmetry-Aware Transformer Training for Automated Planning
by: Fritzsche, Markus, et al.
Published: (2025)
by: Fritzsche, Markus, et al.
Published: (2025)
Topology-Aware Revival for Efficient Sparse Training
by: Jin, Meiling, et al.
Published: (2026)
by: Jin, Meiling, et al.
Published: (2026)
Reasoning-Aware Training for Time Series Forecasting
by: Ahamed, Md Atik, et al.
Published: (2026)
by: Ahamed, Md Atik, et al.
Published: (2026)
DAFA: Distance-Aware Fair Adversarial Training
by: Lee, Hyungyu, et al.
Published: (2024)
by: Lee, Hyungyu, et al.
Published: (2024)
Risk Awareness Injection: Calibrating Vision-Language Models for Safety without Compromising Utility
by: Wang, Mengxuan, et al.
Published: (2026)
by: Wang, Mengxuan, et al.
Published: (2026)
Native Reasoning Models: Training Language Models to Reason on Unverifiable Data
by: Wang, Yuanfu, et al.
Published: (2026)
by: Wang, Yuanfu, et al.
Published: (2026)
Exploring Local Explanations of Nonlinear Models Using Animated Linear Projections
by: Spyrison, Nicholas, et al.
Published: (2022)
by: Spyrison, Nicholas, et al.
Published: (2022)
Task-Aware Parameter-Efficient Fine-Tuning of Large Pre-Trained Models at the Edge
by: Hu, Senkang, et al.
Published: (2025)
by: Hu, Senkang, et al.
Published: (2025)
Similar Items
-
Exposing the Achilles' Heel: Evaluating LLMs Ability to Handle Mistakes in Mathematical Reasoning
by: Singh, Joykirat, et al.
Published: (2024) -
Achilles' Heels: Vulnerable Record Identification in Synthetic Data Publishing
by: Meeus, Matthieu, et al.
Published: (2023) -
Generative AI Training and Copyright Law
by: Stober, Sebastian, et al.
Published: (2025) -
Enhancing Smart Farming Through Federated Learning: A Secure, Scalable, and Efficient Approach for AI-Driven Agriculture
by: Janga, Ritesh, et al.
Published: (2025) -
Scaling Laws for Pre-training Agents and World Models
by: Pearce, Tim, et al.
Published: (2024)