Cover Image

Rethinking Memorization Measures and their Implications in Large Language Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ghosh, Bishwamittra, Das, Soumi, Wu, Qinyuan, Khan, Mohammad Aflah, Gummadi, Krishna P., Terzi, Evimaria, Garg, Deepak
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Fine-tuning vs. In-context Learning in Large Language Models: A Formal Language Learning Perspective
by: Ghosh, Bishwamittra, et al.
Published: (2026)

Understanding Memorisation in LLMs: Dynamics, Influencing Factors, and Implications
by: Speicher, Till, et al.
Published: (2024)

Towards Reliable Latent Knowledge Estimation in LLMs: Zero-Prompt Many-Shot Based Factual Knowledge Extraction
by: Wu, Qinyuan, et al.
Published: (2024)

Revisiting Privacy, Utility, and Efficiency Trade-offs when Fine-Tuning Large Language Models
by: Das, Soumi, et al.
Published: (2025)

Rote Learning Considered Useful: Generalizing over Memorized Data in LLMs
by: Wu, Qinyuan, et al.
Published: (2025)

In Agents We Trust, but Who Do Agents Trust? Latent Source Preferences Steer LLM Generations
by: Khan, Mohammad Aflah, et al.
Published: (2026)

Fractional Rotation, Full Potential? Investigating Performance and Convergence of Partial RoPE
by: Khan, Mohammad Aflah, et al.
Published: (2026)

Hubble: a Model Suite to Advance the Study of LLM Memorization
by: Wei, Johnny Tian-Zheng, et al.
Published: (2025)

LoRA on the Go: Instance-level Dynamic LoRA Selection and Merging
by: Lee, Seungeon, et al.
Published: (2025)

A QUBO Framework for Team Formation
by: Vombatkere, Karan, et al.
Published: (2025)

Understanding team collapse via probabilistic graphical models
by: Nikolaou, Iasonas, et al.
Published: (2024)

Online Two-Stage Submodular Maximization
by: Nikolaou, Iasonas, et al.
Published: (2025)

FACEGroup: Feasible and Actionable Counterfactual Explanations for Group Fairness
by: Fragkathoulas, Christos, et al.
Published: (2024)

Active Fourier Auditor for Estimating Distributional Properties of ML Models
by: Ajarra, Ayoub, et al.
Published: (2024)

Online Submodular Maximization via Online Convex Optimization
by: Salem, Tareq Si, et al.
Published: (2023)

Understanding the Role of Invariance in Transfer Learning
by: Speicher, Till, et al.
Published: (2024)

Large Language Models Memorize Sensor Datasets! Implications on Human Activity Recognition Research
by: Haresamudram, Harish, et al.
Published: (2024)

Prior Aware Memorization: An Efficient Metric for Distinguishing Memorization from Generalization in Large Language Models
by: Tiwari, Trishita, et al.
Published: (2026)

Demystifying Verbatim Memorization in Large Language Models
by: Huang, Jing, et al.
Published: (2024)

Detecting Memorization in Large Language Models
by: Slonski, Eduardo
Published: (2024)

Mitigating Memorization In Language Models
by: Sakarvadia, Mansi, et al.
Published: (2024)

Reason to Rote: Rethinking Memorization in Reasoning
by: Du, Yupei, et al.
Published: (2025)

Computing Approximate Pareto Frontiers for Submodular Utility and Cost Tradeoffs
by: Vombatkere, Karan, et al.
Published: (2026)

Team Formation amidst Conflicts
by: Nikolaou, Iasonas, et al.
Published: (2024)

Inferring the Size of Large Language Models From Popular Text Memorization
by: Nikolic, Ivica
Published: (2026)

Are Large Language Models Memorizing Bug Benchmarks?
by: Ramos, Daniel, et al.
Published: (2024)

GPTQT: Quantize Large Language Models Twice to Push the Efficiency
by: Guo, Yipin, et al.
Published: (2024)

Investigating the Effects of Fairness Interventions Using Pointwise Representational Similarity
by: Kolling, Camila, et al.
Published: (2023)

Measuring Moral Inconsistencies in Large Language Models
by: Bonagiri, Vamshi Krishna, et al.
Published: (2024)

Beyond Frequency: The Role of Redundancy in Large Language Model Memorization
by: Zhang, Jie, et al.
Published: (2025)

Analyzing Memorization in Large Language Models through the Lens of Model Attribution
by: Menta, Tarun Ram, et al.
Published: (2025)

An Evaluation on Large Language Model Outputs: Discourse and Memorization
by: de Wynter, Adrian, et al.
Published: (2023)

Skewed Memorization in Large Language Models: Quantification and Decomposition
by: Li, Hao, et al.
Published: (2025)

A Data-Driven Defense against Edge-case Model Poisoning Attacks on Federated Learning
by: Purohit, Kiran, et al.
Published: (2023)

Rethinking LLM Memorization through the Lens of Adversarial Compression
by: Schwarzschild, Avi, et al.
Published: (2024)

Unlocking Memorization in Large Language Models with Dynamic Soft Prompting
by: Wang, Zhepeng, et al.
Published: (2024)

The Pitfalls of Memorization: When Memorization Hurts Generalization
by: Bayat, Reza, et al.
Published: (2024)

Rethinking Prompt Optimization: Reinforcement, Diversification, and Migration in Blackbox LLMs
by: Davari, MohammadReza, et al.
Published: (2025)

FFN Fusion: Rethinking Sequential Computation in Large Language Models
by: Bercovich, Akhiad, et al.
Published: (2025)

Pruning as a Defense: Reducing Memorization in Large Language Models
by: Gupta, Mansi, et al.
Published: (2025)