Papers
Particle Denoising Diffusion Sampler
Angus Phillips, Hai-Dang Dau, Michael John Hutchinson et al.
PASOA- PArticle baSed Bayesian Optimal Adaptive design
Jacopo Iollo, Christophe Heinkelé, Pierre Alliez et al.
Patchscopes: A Unifying Framework for Inspecting Hidden Representations of Language Models
Asma Ghandeharioun, Avi Caciularu, Adam Pearce et al.
Path-Guided Particle-based Sampling
Mingzhou Fan, Ruida Zhou, Chao Tian et al.
Pausing Policy Learning in Non-stationary Reinforcement Learning
Hyunin Lee, Ming Jin, Javad Lavaei et al.
PcLast: Discovering Plannable Continuous Latent States
Anurag Koul, Shivakanth Sujit, Shaoru Chen et al.
PDHG-Unrolled Learning-to-Optimize Method for Large-Scale Linear Programming
Bingheng Li, Linxin Yang, Yupeng Chen et al.
PEARL: Zero-shot Cross-task Preference Alignment and Robust Reward Learning for Robotic Manipulation
Runze Liu, Yali Du, Fengshuo Bai et al.
Pedestrian Attribute Recognition as Label-balanced Multi-label Learning
Yibo Zhou, Hai-Miao Hu, Yirong Xiang et al.
Peeking with PEAK: Sequential, Nonparametric Composite Hypothesis Tests for Means of Multiple Data Streams
Brian M Cho, Kyra Gan, Nathan Kallus
PerceptAnon: Exploring the Human Perception of Image Anonymization Beyond Pseudonymization for GDPR
Kartik Patwari, Chen-Nee Chuah, Lingjuan Lyu et al.
Perfect Alignment May be Poisonous to Graph Contrastive Learning
Jingyu Liu, Huayi Tang, Yong Liu
Performance Bounds for Active Binary Testing with Information Maximization
Aditya Chattopadhyay, Benjamin David Haeffele, Rene Vidal et al.
Performative Prediction with Bandit Feedback: Learning through Reparameterization
Yatong Chen, Wei Tang, Chien-Ju Ho et al.
Perturb-and-Project: Differentially Private Similarities and Marginals
Vincent Cohen-Addad, Tommaso D’Orsi, Alessandro Epasto et al.
Pessimism Meets Risk: Risk-Sensitive Offline Reinforcement Learning
Dake Zhang, Boxiang Lyu, Shuang Qiu et al.
PGODE: Towards High-quality System Dynamics Modeling
Xiao Luo, Yiyang Gu, Huiyu Jiang et al.
Physics and Lie symmetry informed Gaussian processes
David Dalton, Dirk Husmeier, Hao Gao
Physics-Informed Neural Network Policy Iteration: Algorithms, Convergence, and Verification
Yiming Meng, Ruikun Zhou, Amartya Mukherjee et al.
Physics of Language Models: Part 3.1, Knowledge Storage and Extraction
Zeyuan Allen-Zhu, Yuanzhi Li
PICLe: Eliciting Diverse Behaviors from Large Language Models with Persona In-Context Learning
Hyeong Kyu Choi, Yixuan Li
PIDformer: Transformer Meets Control Theory
Tam Minh Nguyen, Cesar A Uribe, Tan Minh Nguyen et al.
PID: Prompt-Independent Data Protection Against Latent Diffusion Models
Ang Li, Yichuan Mo, Mingjie Li et al.
Pi-DUAL: Using privileged information to distinguish clean from noisy labels
Ke Wang, Guillermo Ortiz-Jimenez, Rodolphe Jenatton et al.
Piecewise Constant and Linear Regression Trees: An Optimal Dynamic Programming Approach
Mim Van Den Bos, Jacobus G. M. Van Der Linden, Emir Demirović