:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Ngong, Ivoline C., Reza, Zarreen, Near, Joseph P.
Format:	Preprint
Published:	2026
Subjects:	Artificial Intelligence
Online Access:	https://arxiv.org/abs/2603.04894
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Differentially Private Learning Needs Better Model Initialization and Self-Distillation
by: Ngong, Ivoline C., et al.
Published: (2024)

Beyond Fixed Psychological Personas: State Beats Trait, but Language Models are State-Blind
by: Harry, Tamunotonye, et al.
Published: (2026)

Distributed HDMM: Scalable, Distributed, Accurate, and Differentially Private Query Workloads without a Trusted Curator
by: Sedimo, Ratang, et al.
Published: (2025)

Evaluating the Usability of Differential Privacy Tools with Data Practitioners
by: Ngong, Ivoline C., et al.
Published: (2023)

OLYMPIA: A Simulation Framework for Evaluating the Concrete Scalability of Secure Aggregation Protocols
by: Ngong, Ivoline C., et al.
Published: (2023)

The Social Laboratory: A Psychometric Framework for Multi-Agent LLM Evaluation
by: Reza, Zarreen
Published: (2025)

AgentSCOPE: Evaluating Contextual Privacy Across Agentic Workflows
by: Ngong, Ivoline C., et al.
Published: (2026)

SoK: Usability Studies in Differential Privacy
by: Dibia, Onyinye, et al.
Published: (2024)

Chopping Trees: Semantic Similarity Based Dynamic Pruning for Tree-of-Thought Reasoning
by: Kim, Joongho, et al.
Published: (2025)

Protecting Users From Themselves: Safeguarding Contextual Privacy in Interactions with Conversational Agents
by: Ngong, Ivoline, et al.
Published: (2025)

Small Models, Big Support: A Local LLM Framework for Educator-Centric Content Creation and Assessment with RAG and CAG
by: Reza, Zarreen, et al.
Published: (2025)

Locally Differentially Private In-Context Learning
by: Zheng, Chunyan, et al.
Published: (2024)

Public Data Assisted Differentially Private In-Context Learning
by: Joo, Seongho, et al.
Published: (2025)

Low-rank finetuning for LLMs: A fairness perspective
by: Das, Saswat, et al.
Published: (2024)

Differentially Private In-Context Learning with Nearest Neighbor Search
by: Koskela, Antti, et al.
Published: (2025)

Data-adaptive Differentially Private Prompt Synthesis for In-Context Learning
by: Gao, Fengyu, et al.
Published: (2024)

DP-TabICL: In-Context Learning with Differentially Private Tabular Data
by: Carey, Alycia N., et al.
Published: (2024)

Differential Multimodal Transformers
by: Li, Jerry, et al.
Published: (2025)

Differentially Private Federated Quantum Learning via Quantum Noise
by: Pokharel, Atit, et al.
Published: (2025)

Differentially Private Multimodal Laplacian Dropout (DP-MLD) for EEG Representative Learning
by: Fu, Xiaowen, et al.
Published: (2024)

Differentially Private Synthetic Data Generation Using Context-Aware GANs
by: Kotal, Anantaa, et al.
Published: (2025)

ContextNav: Towards Agentic Multimodal In-Context Learning
by: Fu, Honghao, et al.
Published: (2025)

An Adaptive Differentially Private Federated Learning Framework with Bi-level Optimization
by: Wang, Jin, et al.
Published: (2026)

Learning with Differentially Private (Sliced) Wasserstein Gradients
by: Rodríguez-Vítores, David, et al.
Published: (2025)

GraMFedDHAR: Graph Based Multimodal Differentially Private Federated HAR
by: Halder, Labani, et al.
Published: (2025)

Towards Differentially Private Reinforcement Learning with General Function Approximation
by: He, Yi, et al.
Published: (2026)

Dual-Priv Pruning : Efficient Differential Private Fine-Tuning in Multimodal Large Language Models
by: Wei, Qianshan, et al.
Published: (2025)

Multimodal Contrastive In-Context Learning
by: Miyanishi, Yosuke, et al.
Published: (2024)

dpmm: Differentially Private Marginal Models, a Library for Synthetic Tabular Data Generation
by: Mahiou, Sofiane, et al.
Published: (2025)

Differentially Private Deep Model-Based Reinforcement Learning
by: Rio, Alexandre, et al.
Published: (2024)

Statistical Limits and Efficient Algorithms for Differentially Private Federated Learning
by: Auddy, Arnab, et al.
Published: (2026)

Differentially Private Reinforcement Learning with Self-Play
by: Qiao, Dan, et al.
Published: (2024)

Generalizing Differentially Private Decentralized Deep Learning with Multi-Agent Consensus
by: Bayrooti, Jasmine, et al.
Published: (2023)

Differentially Private Model Merging
by: Yin, Qichuan, et al.
Published: (2026)

Differentially Private Condorcet Voting
by: Li, Zhechen, et al.
Published: (2022)

From Private to Public: Benchmarking GANs in the Context of Private Time Series Classification
by: Mercier, Dominique, et al.
Published: (2023)

Mimic In-Context Learning for Multimodal Tasks
by: Jiang, Yuchu, et al.
Published: (2025)

Differentially Private Block-wise Gradient Shuffle for Deep Learning
by: Zagardo, David
Published: (2024)

Privacy-Preserving Federated Learning with Differentially Private Hyperdimensional Computing
by: Piran, Fardin Jalil, et al.
Published: (2024)

Differentially Private Federated Clustering with Random Rebalancing
by: Yang, Xiyuan, et al.
Published: (2025)