Revisiting Privacy, Utility, and Efficiency Trade-offs when Fine-Tuning Large Language Models
Fuente:
arXiv
Saved in:
| Main Authors: | Das, Soumi, Kolling, Camila, Khan, Mohammad Aflah, Amani, Mahsa, Ghosh, Bishwamittra, Wu, Qinyuan, Speicher, Till, Gummadi, Krishna P. |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| 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)
by: Ghosh, Bishwamittra, et al.
Published: (2026)
Rote Learning Considered Useful: Generalizing over Memorized Data in LLMs
by: Wu, Qinyuan, et al.
Published: (2025)
by: Wu, Qinyuan, et al.
Published: (2025)
Understanding Memorisation in LLMs: Dynamics, Influencing Factors, and Implications
by: Speicher, Till, et al.
Published: (2024)
by: Speicher, Till, et al.
Published: (2024)
In Agents We Trust, but Who Do Agents Trust? Latent Source Preferences Steer LLM Generations
by: Khan, Mohammad Aflah, et al.
Published: (2026)
by: Khan, Mohammad Aflah, et al.
Published: (2026)
Towards Reliable Latent Knowledge Estimation in LLMs: Zero-Prompt Many-Shot Based Factual Knowledge Extraction
by: Wu, Qinyuan, et al.
Published: (2024)
by: Wu, Qinyuan, et al.
Published: (2024)
Rethinking Memorization Measures and their Implications in Large Language Models
by: Ghosh, Bishwamittra, et al.
Published: (2025)
by: Ghosh, Bishwamittra, et al.
Published: (2025)
Investigating the Effects of Fairness Interventions Using Pointwise Representational Similarity
by: Kolling, Camila, et al.
Published: (2023)
by: Kolling, Camila, et al.
Published: (2023)
Understanding the Role of Invariance in Transfer Learning
by: Speicher, Till, et al.
Published: (2024)
by: Speicher, Till, et al.
Published: (2024)
To Call or Not to Call: A Framework to Assess and Optimize LLM Tool Calling
by: Wu, Qinyuan, et al.
Published: (2026)
by: Wu, Qinyuan, et al.
Published: (2026)
Fractional Rotation, Full Potential? Investigating Performance and Convergence of Partial RoPE
by: Khan, Mohammad Aflah, et al.
Published: (2026)
by: Khan, Mohammad Aflah, et al.
Published: (2026)
Synthetic Data: Revisiting the Privacy-Utility Trade-off
by: Sarmin, Fatima Jahan, et al.
Published: (2024)
by: Sarmin, Fatima Jahan, et al.
Published: (2024)
LoRA on the Go: Instance-level Dynamic LoRA Selection and Merging
by: Lee, Seungeon, et al.
Published: (2025)
by: Lee, Seungeon, et al.
Published: (2025)
Revisiting Privacy-Utility Trade-off for DP Training with Pre-existing Knowledge
by: Zheng, Yu, et al.
Published: (2024)
by: Zheng, Yu, et al.
Published: (2024)
The Privacy-Utility Trade-off in the Topics API
by: Alvim, Mário S., et al.
Published: (2024)
by: Alvim, Mário S., et al.
Published: (2024)
Enhancing Trade-offs in Privacy, Utility, and Computational Efficiency through MUltistage Sampling Technique (MUST)
by: Zhao, Xingyuan, et al.
Published: (2023)
by: Zhao, Xingyuan, et al.
Published: (2023)
Privacy-Utility-Bias Trade-offs for Privacy-Preserving Recommender Systems
by: Parsarad, Shiva, et al.
Published: (2025)
by: Parsarad, Shiva, et al.
Published: (2025)
Revisiting Locally Differentially Private Protocols: Towards Better Trade-offs in Privacy, Utility, and Attack Resistance
by: Arcolezi, Héber H., et al.
Published: (2025)
by: Arcolezi, Héber H., et al.
Published: (2025)
The Algorithmic Self-Portrait: Deconstructing Memory in ChatGPT
by: Dash, Abhisek, et al.
Published: (2026)
by: Dash, Abhisek, et al.
Published: (2026)
TokenSmith: Streamlining Data Editing, Search, and Inspection for Large-Scale Language Model Training and Interpretability
by: Khan, Mohammad Aflah, et al.
Published: (2025)
by: Khan, Mohammad Aflah, et al.
Published: (2025)
Enhancing Privacy-Utility Trade-offs to Mitigate Memorization in Diffusion Models
by: Chen, Chen, et al.
Published: (2025)
by: Chen, Chen, et al.
Published: (2025)
The Users' Perspective on the Privacy-Utility Trade-offs in Health Recommender Systems
by: Valdez, André Calero, et al.
Published: (2018)
by: Valdez, André Calero, et al.
Published: (2018)
Position: Embodied AI Requires a Privacy-Utility Trade-off
by: Fan, Xiaoliang, et al.
Published: (2026)
by: Fan, Xiaoliang, et al.
Published: (2026)
The Privacy-Utility Trade-Off of Location Tracking in Ad Personalization
by: Mosaffa, Mohammad, et al.
Published: (2026)
by: Mosaffa, Mohammad, et al.
Published: (2026)
Cluster-guided LLM-Based Anonymization of Software Analytics Data: Studying Privacy-Utility Trade-offs in JIT Defect Prediction
by: Khan, Maaz, et al.
Published: (2025)
by: Khan, Maaz, et al.
Published: (2025)
Mitigating Privacy-Utility Trade-off in Decentralized Federated Learning via $f$-Differential Privacy
by: Li, Xiang, et al.
Published: (2025)
by: Li, Xiang, et al.
Published: (2025)
Logical Consistency of Large Language Models in Fact-checking
by: Ghosh, Bishwamittra, et al.
Published: (2024)
by: Ghosh, Bishwamittra, et al.
Published: (2024)
A Framework for Evaluating Privacy-Utility Trade-off in Vertical Federated Learning
by: Kang, Yan, et al.
Published: (2022)
by: Kang, Yan, et al.
Published: (2022)
Optimizing Privacy-Utility Trade-off in Decentralized Learning with Generalized Correlated Noise
by: Rodio, Angelo, et al.
Published: (2025)
by: Rodio, Angelo, et al.
Published: (2025)
Active Fourier Auditor for Estimating Distributional Properties of ML Models
by: Ajarra, Ayoub, et al.
Published: (2024)
by: Ajarra, Ayoub, et al.
Published: (2024)
A Comparative Analysis of Word-Level Metric Differential Privacy: Benchmarking The Privacy-Utility Trade-off
by: Meisenbacher, Stephen, et al.
Published: (2024)
by: Meisenbacher, Stephen, et al.
Published: (2024)
POLAR-Bench: A Diagnostic Benchmark for Privacy-Utility Trade-offs in LLM Agents
by: Zheng, Qiaoyuan, et al.
Published: (2026)
by: Zheng, Qiaoyuan, et al.
Published: (2026)
Adaptive Text Anonymization: Learning Privacy-Utility Trade-offs via Prompt Optimization
by: Loiseau, Gabriel, et al.
Published: (2026)
by: Loiseau, Gabriel, et al.
Published: (2026)
Long-Term Conversation Analysis: Privacy-Utility Trade-off under Noise and Reverberation
by: Pohlhausen, Jule, et al.
Published: (2024)
by: Pohlhausen, Jule, et al.
Published: (2024)
Position: Life-Logging Video Streams Make the Privacy-Utility Trade-off Inevitable
by: Zou, Tianyuan, et al.
Published: (2026)
by: Zou, Tianyuan, et al.
Published: (2026)
Privacy-Utility Trade-offs Under Multi-Level Point-Wise Leakage Constraints
by: Zamani, Amirreza, et al.
Published: (2026)
by: Zamani, Amirreza, et al.
Published: (2026)
Hubble: a Model Suite to Advance the Study of LLM Memorization
by: Wei, Johnny Tian-Zheng, et al.
Published: (2025)
by: Wei, Johnny Tian-Zheng, et al.
Published: (2025)
Lost in Tokenization: Fundamental Trade-offs in Graph Tokenization for Transformers
by: Bechler-Speicher, Maya, et al.
Published: (2026)
by: Bechler-Speicher, Maya, et al.
Published: (2026)
Misclassification Rate and Privacy-Utility Trade-offs in Graph Convolutional Networks via Subsampling Stability
by: Zhang, Yexin, et al.
Published: (2026)
by: Zhang, Yexin, et al.
Published: (2026)
IDDM: Identity-Decoupled Personalized Diffusion Models with a Tunable Privacy-Utility Trade-off
by: Dai, Linyan, et al.
Published: (2026)
by: Dai, Linyan, et al.
Published: (2026)
Clients Collaborate: Flexible Differentially Private Federated Learning with Guaranteed Improvement of Utility-Privacy Trade-off
by: Li, Yuecheng, et al.
Published: (2024)
by: Li, Yuecheng, et al.
Published: (2024)
Similar Items
-
Fine-tuning vs. In-context Learning in Large Language Models: A Formal Language Learning Perspective
by: Ghosh, Bishwamittra, et al.
Published: (2026) -
Rote Learning Considered Useful: Generalizing over Memorized Data in LLMs
by: Wu, Qinyuan, et al.
Published: (2025) -
Understanding Memorisation in LLMs: Dynamics, Influencing Factors, and Implications
by: Speicher, Till, et al.
Published: (2024) -
In Agents We Trust, but Who Do Agents Trust? Latent Source Preferences Steer LLM Generations
by: Khan, Mohammad Aflah, et al.
Published: (2026) -
Towards Reliable Latent Knowledge Estimation in LLMs: Zero-Prompt Many-Shot Based Factual Knowledge Extraction
by: Wu, Qinyuan, et al.
Published: (2024)