Papers
Privacy Amplification Through Synthetic Data: Insights from Linear Regression
Clément Pierquin, Aurélien Bellet, Marc Tommasi et al.
Privacy Attacks on Image AutoRegressive Models
Antoni Kowalczuk, Jan Dubiński, Franziska Boenisch et al.
Privacy-Preserving Federated Convex Optimization: Balancing Partial-Participation and Efficiency via Noise Cancellation
Roie Reshef, Kfir Yehuda Levy
Privacy-Shielded Image Compression: Defending Against Exploitation from Vision-Language Pretrained Models
Xuelin Shen, Jiayin Xu, Kangsheng Yin et al.
Private Federated Learning using Preference-Optimized Synthetic Data
Charlie Hou, Mei-Yu Wang, Yige Zhu et al.
Private Lossless Multiple Release
Joel Daniel Andersson, Lukas Retschmeier, Boel Nelson et al.
Private Model Personalization Revisited
Conor Snedeker, Xinyu Zhou, Raef Bassily
Proactive Agents for Multi-Turn Text-to-Image Generation Under Uncertainty
Meera Hahn, Wenjun Zeng, Nithish Kannen et al.
Probabilistic Factorial Experimental Design for Combinatorial Interventions
Divya Shyamal, Jiaqi Zhang, Caroline Uhler
Probabilistic Group Mask Guided Discrete Optimization for Incremental Learning
Fengqiang Wan, Yang Yang
Probabilistic Interactive 3D Segmentation with Hierarchical Neural Processes
Jie Liu, Pan Zhou, Zehao Xiao et al.
Probably Approximately Global Robustness Certification
Peter Blohm, Patrick Indri, Thomas Gärtner et al.
Probing Visual Language Priors in VLMs
Tiange Luo, Ang Cao, Gunhee Lee et al.
Procurement Auctions via Approximately Optimal Submodular Optimization
Yuan Deng, Amin Karbasi, Vahab Mirrokni et al.
ProDiff: Prototype-Guided Diffusion for Minimal Information Trajectory Imputation
Tianci Bu, Le Zhou, Wenchuan Yang et al.
Product of Experts with LLMs: Boosting Performance on ARC Is a Matter of Perspective
Daniel Franzen, Jan Disselhoff, David Hartmann
Programming Every Example: Lifting Pre-training Data Quality Like Experts at Scale
Fan Zhou, Zengzhi Wang, Qian Liu et al.
Progressively Label Enhancement for Large Language Model Alignment
Biao Liu, Ning Xu, Xin Geng
Progressive Tempering Sampler with Diffusion
Severi Rissanen, Ruikang Ouyang, Jiajun He et al.
Projection Optimization: A General Framework for Multi-Objective and Multi-Group RLHF
Nuoya Xiong, Aarti Singh
Projection Pursuit Density Ratio Estimation
Meilin Wang, Wei Huang, Mingming Gong et al.
Promoting Ensemble Diversity with Interactive Bayesian Distributional Robustness for Fine-tuning Foundation Models
Ngoc-Quan Pham, Tuan Truong, Quyen Tran et al.
Prompt-based Depth Pruning of Large Language Models
Juyun Wee, Minjae Park, Jaeho Lee
Prompt-to-Leaderboard: Prompt-Adaptive LLM Evaluations
Evan Frick, Connor Chen, Joseph Tennyson et al.
ProofAug: Efficient Neural Theorem Proving via Fine-grained Proof Structure Analysis
Haoxiong Liu, Jiacheng Sun, Zhenguo Li et al.