Papers
Hierarchical Planning for Complex Tasks with Knowledge Graph-RAG and Symbolic Verification
Flavio Petruzzellis, Cristina Cornelio, Pietro Lio
Training Deep Learning Models with Norm-Constrained LMOs
Thomas Pethick, Wanyun Xie, Kimon Antonakopoulos et al.
Partition First, Embed Later: Laplacian-Based Feature Partitioning for Refined Embedding and Visualization of High-Dimensional Data
Erez Peterfreund, Ofir Lindenbaum, Yuval Kluger et al.
Adjusting Model Size in Continual Gaussian Processes: How Big is Big Enough?
Guiomar Pescador-Barrios, Sarah Lucie Filippi, Mark Van Der Wilk
Mechanistic PDE Networks for Discovery of Governing Equations
Adeel Pervez, Efstratios Gavves, Francesco Locatello
Revisiting the Predictability of Performative, Social Events
Juan Carlos Perdomo
Noise Conditional Variational Score Distillation
Xinyu Peng, Ziyang Zheng, Yaoming Wang et al.
Circumventing Backdoor Space via Weight Symmetry
Jie Peng, Hongwei Yang, Jing Zhao et al.
CAT: Contrastive Adversarial Training for Evaluating the Robustness of Protective Perturbations in Latent Diffusion Models
Sen Peng, Mingyue Wang, Jianfei He et al.
A Near Linear Query Lower Bound for Submodular Maximization
Binghui Peng, Aviad Rubinstein
KGMark: A Diffusion Watermark for Knowledge Graphs
Hongrui Peng, Haolang Lu, Yuanlong Yu et al.
Conformal Prediction with Cellwise Outliers: A Detect-then-Impute Approach
Qian Peng, Yajie Bao, Haojie Ren et al.
Modalities Contribute Unequally: Enhancing Medical Multi-modal Learning through Adaptive Modality Token Re-balancing
Jie Peng, Jenna L. Ballard, Mohan Zhang et al.
Addressing Concept Mislabeling in Concept Bottleneck Models Through Preference Optimization
Emiliano Penaloza, Tianyue H. Zhang, Laurent Charlin et al.
Approximating Latent Manifolds in Neural Networks via Vanishing Ideals
Nico Pelleriti, Max Zimmer, Elias Samuel Wirth et al.
Hyper-Transforming Latent Diffusion Models
Ignacio Peis, Batuhan Koyuncu, Isabel Valera et al.
GoIRL: Graph-Oriented Inverse Reinforcement Learning for Multimodal Trajectory Prediction
Muleilan Pei, Shaoshuai Shi, Lu Zhang et al.
Diffusion-based Adversarial Purification from the Perspective of the Frequency Domain
Gaozheng Pei, Ke Ma, Yingfei Sun et al.
Non-Stationary Predictions May Be More Informative: Exploring Pseudo-Labels with a Two-Phase Pattern of Training Dynamics
Hongbin Pei, Jingxin Hai, Yu Li et al.
Thermalizer: Stable autoregressive neural emulation of spatiotemporal chaos
Christian Pedersen, Laure Zanna, Joan Bruna
Permutation Equivariant Neural Networks for Symmetric Tensors
Edward Pearce-Crump
Compact Matrix Quantum Group Equivariant Neural Networks
Edward Pearce-Crump
Scaling Laws for Pre-training Agents and World Models
Tim Pearce, Tabish Rashid, David Bignell et al.
Representative Language Generation
Charlotte Peale, Vinod Raman, Omer Reingold
Stable Offline Value Function Learning with Bisimulation-based Representations
Brahma S Pavse, Yudong Chen, Qiaomin Xie et al.