:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Zhang, Jie, Zhao, Qinghua, Lin, Chi-ho, Kang, Zhongfeng, Li, Lei
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	https://arxiv.org/abs/2506.12321
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Layer-wise Analysis of Supervised Fine-Tuning
by: Zhao, Qinghua, et al.
Published: (2026)

Beyond Memorization: Violating Privacy Via Inference with Large Language Models
by: Staab, Robin, et al.
Published: (2023)

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

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

Beyond Redundancy: Information-aware Unsupervised Multiplex Graph Structure Learning
by: Shen, Zhixiang, et al.
Published: (2024)

Efficient Arbitrary Precision Acceleration for Large Language Models on GPU Tensor Cores
by: Ma, Shaobo, et al.
Published: (2024)

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

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

Exploring Memorization in Fine-tuned Language Models
by: Zeng, Shenglai, et al.
Published: (2023)

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

Bridging Visualization and Optimization: Multimodal Large Language Models on Graph-Structured Combinatorial Optimization
by: Zhao, Jie, et al.
Published: (2025)

The Role of Deductive and Inductive Reasoning in Large Language Models
by: Cai, Chengkun, et al.
Published: (2024)

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

REMA: A Unified Reasoning Manifold Framework for Interpreting Large Language Model
by: Li, Bo, et al.
Published: (2025)

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

NASH: Neural Architecture and Accelerator Search for Multiplication-Reduced Hybrid Models
by: Xu, Yang, et al.
Published: (2024)

ClimateLLM: Efficient Weather Forecasting via Frequency-Aware Large Language Models
by: Li, Shixuan, et al.
Published: (2025)

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

Memorize and Rank: Elevating Large Language Models for Clinical Diagnosis Prediction
by: Ma, Mingyu Derek, et al.
Published: (2025)

On Memorization in Diffusion Models
by: Gu, Xiangming, et al.
Published: (2023)

Structure and Redundancy in Large Language Models: A Spectral Study via Random Matrix Theory
by: Ettori, Davide
Published: (2026)

Elephants Never Forget: Memorization and Learning of Tabular Data in Large Language Models
by: Bordt, Sebastian, et al.
Published: (2024)

TEON: Tensorized Orthonormalization Beyond Layer-Wise Muon for Large Language Model Pre-Training
by: Zhang, Ruijie, et al.
Published: (2026)

Beyond Correctness: Confidence-Aware Reward Modeling for Enhancing Large Language Model Reasoning
by: He, Qianxi, et al.
Published: (2025)

Beyond Redundancy: Diverse and Specialized Multi-Expert Sparse Autoencoder
by: Xu, Zhen, et al.
Published: (2025)

Maximum Redundancy Pruning: A Principle-Driven Layerwise Sparsity Allocation for LLMs
by: Gao, Chang, et al.
Published: (2025)

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

Multi-Objective Large Language Model Unlearning
by: Pan, Zibin, et al.
Published: (2024)

Ratio law: mathematical descriptions for a universal relationship between AI performance and input samples
by: Kang, Boming, et al.
Published: (2024)

Beyond Reward Hacking: Causal Rewards for Large Language Model Alignment
by: Wang, Chaoqi, et al.
Published: (2025)

Memorization Sinks: Isolating Memorization during LLM Training
by: Ghosal, Gaurav R., et al.
Published: (2025)

Token Reduction Should Go Beyond Efficiency in Generative Models -- From Vision, Language to Multimodality
by: Kong, Zhenglun, et al.
Published: (2025)

On the Memorization of Consistency Distillation for Diffusion Models
by: Jiang, Bingqing, et al.
Published: (2026)

Instruction Mining: Instruction Data Selection for Tuning Large Language Models
by: Cao, Yihan, et al.
Published: (2023)

$R^2$-dLLM: Accelerating Diffusion Large Language Models via Spatio-Temporal Redundancy Reduction
by: Du, Zhenbang, et al.
Published: (2026)

Quantifying Memorization and Parametric Response Rates in Retrieval-Augmented Vision-Language Models
by: Carragher, Peter, et al.
Published: (2025)

Memorize Theorems, Not Instances: Probing SFT Generalization through Mathematical Reasoning
by: Peng, Ruiying, et al.
Published: (2026)

To Each (Textual Sequence) Its Own: Improving Memorized-Data Unlearning in Large Language Models
by: Barbulescu, George-Octavian, et al.
Published: (2024)

RoleCraft-GLM: Advancing Personalized Role-Playing in Large Language Models
by: Tao, Meiling, et al.
Published: (2023)

Generalizability of Memorization Neural Networks
by: Yu, Lijia, et al.
Published: (2024)