All Papers

Practical Hamiltonian Monte Carlo on Riemannian Manifolds via Relativity Theory

Kai Xu, Hong Ge

Practical Measurements of Translucent Materials with Inter-Pixel Translucency Prior

Zhenyu Chen, Jie Guo, Shuichang Lai et al.

Practical Performance Guarantees for Pipelined DNN Inference

Aaron Archer, Matthew Fahrbach, Kuikui Liu et al.

Practical Privacy-Preserving MLaaS: When Compressive Sensing Meets Generative Networks

Jia Wang, Wuqiang Su, Zushu Huang et al.

Pragmatic Feature Preferences: Learning Reward-Relevant Preferences from Human Input

Andi Peng, Yuying Sun, Tianmin Shu et al.

PRDP: Proximal Reward Difference Prediction for Large-Scale Reward Finetuning of Diffusion Models

Fei Deng, Qifei Wang, Wei Wei et al.

Precise Accuracy / Robustness Tradeoffs in Regression: Case of General Norms

Elvis Dohmatob, Meyer Scetbon

PreciseControl: Enhancing Text-To-Image Diffusion Models with Fine-Grained Attribute Control

Rishubh Parihar, Sachidanand VS, Sabariswaran Mani et al.

PredBench: Benchmarking Spatio-Temporal Prediction across Diverse Disciplines

Zidong Wang, Zeyu Lu, Di Huang et al.

Predicated Diffusion: Predicate Logic-Based Attention Guidance for Text-to-Image Diffusion Models

Kota Sueyoshi, Takashi Matsubara

Predicting and Interpreting Energy Barriers of Metallic Glasses with Graph Neural Networks

Haoyu Li, Shichang Zhang, Longwen Tang et al.

Predicting Dose-Response Curves with Deep Neural Networks

Pedro A. Campana, Paul Prasse, Tobias Scheffer

Predicting Emergent Abilities with Infinite Resolution Evaluation

Shengding Hu, Xin Liu, Xu Han et al.

Predicting Lagrangian Multipliers for Mixed Integer Linear Programs

Francesco Demelas, Joseph Roux, Mathieu Lacroix et al.

Predicting Real-World Penny Auction Durations by Integrating Game Theory and Machine Learning

Prediction Accuracy of Learning in Games : Follow-the-Regularized-Leader meets Heisenberg

Yi Feng, Georgios Piliouras, Xiao Wang

Prediction Error-based Classification for Class-Incremental Learning

Michał Zając, Tinne Tuytelaars, Gido M van de Ven

Prediction Exposes Your Face: Black-box Model Inversion via Prediction Alignment

Yufan Liu, Wanqian Zhang, Dayan Wu et al.

Prediction-powered Generalization of Causal Inferences

Ilker Demirel, Ahmed Alaa, Anthony Philippakis et al.

Prediction without Preclusion: Recourse Verification with Reachable Sets

Avni Kothari, Bogdan Kulynych, Tsui-Wei Weng et al.

Predictive auxiliary objectives in deep RL mimic learning in the brain

Ching Fang, Kimberly Stachenfeld

Predictive Coding beyond Correlations

Tommaso Salvatori, Luca Pinchetti, Amine M'Charrak et al.

Predictive Dynamic Fusion

Bing Cao, Yinan Xia, Yi Ding et al.

Predictive Linear Online Tracking for Unknown Targets

Anastasios Tsiamis, Aren Karapetyan, Yueshan Li et al.

Predictive Performance Comparison of Decision Policies Under Confounding

Luke Guerdan, Amanda Coston, Ken Holstein et al.

Predictive, scalable and interpretable knowledge tracing on structured domains

Hanqi Zhou, Robert Bamler, Charley Wu et al.

PredToken: Predicting Unknown Tokens and Beyond with Coarse-to-Fine Iterative Decoding

Xuesong Nie, Haoyuan Jin, Yunfeng Yan et al.

PrefAce: Face-Centric Pretraining with Self-Structure Aware Distillation

Siyuan Hu, Zheng Wang, Peng Hu et al.

Preference Aware Dual Contrastive Learning for Item Cold-Start Recommendation

Wenbo Wang, Bingquan Liu, Lili Shan et al.

Preference Fine-Tuning of LLMs Should Leverage Suboptimal, On-Policy Data

Fahim Tajwar, Anikait Singh, Archit Sharma et al.

Preference Optimization for Molecule Synthesis with Conditional Residual Energy-based Models

Songtao Liu, Hanjun Dai, Yue Zhao et al.

Preference Ranking Optimization for Human Alignment

Feifan Song, Bowen Yu, Minghao Li et al.

PREFER: Prompt Ensemble Learning via Feedback-Reflect-Refine

Chenrui Zhang, Lin Liu, Chuyuan Wang et al.

PREGO: Online Mistake Detection in PRocedural EGOcentric Videos

Alessandro Flaborea, Guido M. D&amp, #x27 et al.

PreLAR: World Model Pre-training with Learnable Action Representation

Lixuan Zhang, Meina Kan, Shiguang Shan et al.

Premier-TACO is a Few-Shot Policy Learner: Pretraining Multitask Representation via Temporal Action-Driven Contrastive Loss

Ruijie Zheng, Yongyuan Liang, xiyao wang et al.

Premise Order Matters in Reasoning with Large Language Models

Xinyun Chen, Ryan Chi, Xuezhi Wang et al.

PreRoutGNN for Timing Prediction with Order Preserving Partition: Global Circuit Pre-training, Local Delay Learning and Attentional Cell Modeling

Ruizhe Zhong, Junjie Ye, Zhentao Tang et al.

Preserving Fairness Generalization in Deepfake Detection

Li Lin, Xinan He, Yan Ju et al.

PreSight: Enhancing Autonomous Vehicle Perception with City-Scale NeRF Priors

Tianyuan Yuan, Mao Yucheng, Jiawei Yang et al.

PRES: Toward Scalable Memory-Based Dynamic Graph Neural Networks

Junwei Su, Difan Zou, Chuan Wu

PrE-Text: Training Language Models on Private Federated Data in the Age of LLMs

Charlie Hou, Akshat Shrivastava, Hongyuan Zhan et al.

PRET: Planning with Directed Fidelity Trajectory for Vision and Language Navigation

Renjie Lu, Jing-Ke Meng, WEISHI ZHENG

Pre-trained Model Guided Fine-Tuning for Zero-Shot Adversarial Robustness

Sibo Wang, Jie Zhang, Zheng Yuan et al.

Pre-trained Vision and Language Transformers Are Few-Shot Incremental Learners

Keon Hee Park, Kyungwoo Song, Gyeong-Moon Park

Pre-trained Visual Dynamics Representations for Efficient Policy Learning

Hao Luo, Bohan Zhou, Zongqing Lu

Pre-Training and Fine-Tuning Generative Flow Networks

Ling Pan, Moksh Jain, Kanika Madan et al.

Pre-Training Goal-based Models for Sample-Efficient Reinforcement Learning

Haoqi Yuan, Zhancun Mu, Feiyang Xie et al.

Pre-training LiDAR-based 3D Object Detectors through Colorization

Tai-Yu Pan, Chenyang Ma, Tianle Chen et al.

Pre-Training Protein Bi-level Representation Through Span Mask Strategy On 3D Protein Chains

Jiale Zhao, Wanru Zhuang, Jia Song et al.