Papers
11,015 papers found
Positive-Unlabeled Diffusion Models for Preventing Sensitive Data Generation
Hiroshi Takahashi, Tomoharu Iwata, Atsutoshi Kumagai et al.
PostCast: Generalizable Postprocessing for Precipitation Nowcasting via Unsupervised Blurriness Modeling
Junchao Gong, Siwei Tu, Weidong Yang et al.
PostEdit: Posterior Sampling for Efficient Zero-Shot Image Editing
Feng Tian, Yixuan Li, Yichao Yan et al.
Posterior-Mean Rectified Flow: Towards Minimum MSE Photo-Realistic Image Restoration
Guy Ohayon, Tomer Michaeli, Michael Elad
Post-hoc Reward Calibration: A Case Study on Length Bias
Zeyu Huang, Zihan Qiu, Zili Wang et al.
POTEC: Off-Policy Contextual Bandits for Large Action Spaces via Policy Decomposition
Yuta Saito, Jihan Yao, Thorsten Joachims
PPT: Patch Order Do Matters In Time Series Pretext Task
Jaeho Kim, Kwangryeol Park, Sukmin Yun et al.
PQMass: Probabilistic Assessment of the Quality of Generative Models using Probability Mass Estimation
Pablo Lemos, Sammy Nasser Sharief, Nikolay Malkin et al.
PRDP: Progressively Refined Differentiable Physics
Kanishk Bhatia, Felix Koehler, Nils Thuerey
Preble: Efficient Distributed Prompt Scheduling for LLM Serving
Vikranth Srivatsa, Zijian He, Reyna Abhyankar et al.
Precedence-Constrained Winter Value for Effective Graph Data Valuation
Hongliang Chi, Wei Jin, Charu C. Aggarwal et al.
Precise Localization of Memories: A Fine-grained Neuron-level Knowledge Editing Technique for LLMs
Haowen Pan, Xiaozhi Wang, Yixin Cao et al.
Precise Parameter Localization for Textual Generation in Diffusion Models
Łukasz Staniszewski, Bartosz Cywiński, Franziska Boenisch et al.
Predicate Hierarchies Improve Few-Shot State Classification
Emily Jin, Joy Hsu, Jiajun Wu
Predicting the Energy Landscape of Stochastic Dynamical System via Physics-informed Self-supervised Learning
Ruikun Li, Huandong Wang, Qingmin Liao et al.
Predictive Inverse Dynamics Models are Scalable Learners for Robotic Manipulation
Yang Tian, Sizhe Yang, Jia Zeng et al.
Predictive Uncertainty Quantification for Bird's Eye View Segmentation: A Benchmark and Novel Loss Function
Linlin Yu, Bowen Yang, Tianhao Wang et al.
Preference Diffusion for Recommendation
Shuo Liu, An Zhang, Guoqing Hu et al.
Preference Elicitation for Offline Reinforcement Learning
Alizée Pace, Bernhard Schölkopf, Gunnar Ratsch et al.
Preference Optimization for Reasoning with Pseudo Feedback
Fangkai Jiao, Geyang Guo, Xingxing Zhang et al.
Preserving Deep Representations in One-Shot Pruning: A Hessian-Free Second-Order Optimization Framework
Ryan Lucas, Rahul Mazumder
Preserving Diversity in Supervised Fine-Tuning of Large Language Models
Ziniu Li, Congliang Chen, Tian Xu et al.
Presto! Distilling Steps and Layers for Accelerating Music Generation
Zachary Novack, Ge Zhu, Jonah Casebeer et al.
Prevalence of Negative Transfer in Continual Reinforcement Learning: Analyses and a Simple Baseline
Hongjoon Ahn, Jinu Hyeon, Youngmin Oh et al.