Poster Papers
24,624 papers found • Page 440 of 493
Conference
Preference Optimization for Molecule Synthesis with Conditional Residual Energy-based Models
Songtao Liu, Hanjun Dai, Yue Zhao et al.
PREGO: Online Mistake Detection in PRocedural EGOcentric Videos
Alessandro Flaborea, Guido M. D&, #x27 et al.
PreLAR: World Model Pre-training with Learnable Action Representation
Lixuan Zhang, Meina Kan, Shiguang Shan et al.
Premise Order Matters in Reasoning with Large Language Models
Xinyun Chen, Ryan Chi, Xuezhi Wang 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.
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 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.
Pre-training Sequence, Structure, and Surface Features for Comprehensive Protein Representation Learning
Youhan Lee, Hasun Yu, Jaemyung Lee et al.
Pre-training Vision Models with Mandelbulb Variations
Benjamin N. Chiche, Yuto Horikawa, Ryo Fujita
Pre-training with Synthetic Data Helps Offline Reinforcement Learning
Zecheng Wang, Che Wang, Zixuan Dong et al.
Preventing Catastrophic Forgetting through Memory Networks in Continuous Detection
Gaurav Bhatt, Leonid Sigal, James Ross
Preventing Catastrophic Overfitting in Fast Adversarial Training: A Bi-level Optimization Perspective
Zhaoxin Wang, Handing Wang, Cong Tian et al.
Preventing Model Collapse in Gaussian Process Latent Variable Models
Ying Li, Zhidi Lin, Feng Yin et al.
Previously on ... From Recaps to Story Summarization
Aditya Kumar Singh, Dhruv Srivastava, Makarand Tapaswi
PRIME: Prioritizing Interpretability in Failure Mode Extraction
Keivan Rezaei, Mehrdad Saberi, Mazda Moayeri et al.
Principled Architecture-aware Scaling of Hyperparameters
Wuyang Chen, Junru Wu, Zhangyang Wang et al.
Principled Federated Domain Adaptation: Gradient Projection and Auto-Weighting
Enyi Jiang, Yibo Jacky Zhang, Sanmi Koyejo
Principled Gradient-Based MCMC for Conditional Sampling of Text
Li Du, Afra Amini, Lucas Torroba Hennigen et al.
Principled Penalty-based Methods for Bilevel Reinforcement Learning and RLHF
Han Shen, Zhuoran Yang, Tianyi Chen
Principled Preferential Bayesian Optimization
Wenjie Xu, Wenbin Wang, Yuning Jiang et al.
Prioritized Semantic Learning for Zero-shot Instance Navigation
Xinyu Sun, Lizhao Liu, Hongyan Zhi et al.
Prioritized Soft Q-Decomposition for Lexicographic Reinforcement Learning
Finn Rietz, Erik Schaffernicht, Stefan Heinrich et al.
Prior Mismatch and Adaptation in PnP-ADMM with a Nonconvex Convergence Analysis
Shirin Shoushtari, JIAMING LIU, Edward Chandler et al.
Prior Specification for Bayesian Matrix Factorization via Prior Predictive Matching
Eliezer de Souza da Silva, Tomasz Kuśmierczyk, Marcelo Hartmann et al.
Prismatic VLMs: Investigating the Design Space of Visually-Conditioned Language Models
Siddharth Karamcheti, Suraj Nair, Ashwin Balakrishna et al.
Privacy Attacks in Decentralized Learning
Abdellah El Mrini, Edwige Cyffers, Aurélien Bellet
Privacy Backdoors: Stealing Data with Corrupted Pretrained Models
Shanglun Feng, Florian Tramer
Privacy Preserving Adaptive Experiment Design
Jiachun Li, Kaining Shi, David Simchi-Levi
Privacy-Preserving Adaptive Re-Identification without Image Transfer
Hamza Rami, Jhony H. Giraldo, Nicolas Winckler et al.
Privacy-Preserving Data Release Leveraging Optimal Transport and Particle Gradient Descent
Konstantin Donhauser, Javier Abad, Neha Hulkund et al.
Privacy-Preserving Embedding via Look-up Table Evaluation with Fully Homomorphic Encryption
Jae-yun Kim, Saerom Park, Joohee Lee et al.
Privacy-Preserving Face Recognition Using Trainable Feature Subtraction
Yuxi Mi, Zhizhou Zhong, Yuge Huang et al.
Privacy-Preserving In-Context Learning for Large Language Models
Tong Wu, Ashwinee Panda, Jiachen (Tianhao) Wang et al.
Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation
Xinyu Tang, Richard Shin, Huseyin Inan et al.
Privacy-Preserving Instructions for Aligning Large Language Models
Da Yu, Peter Kairouz, Sewoong Oh et al.
Privacy-Preserving Optics for Enhancing Protection in Face De-Identification
Jhon Lopez, Carlos Hinojosa, Henry Arguello et al.
Privacy Profiles for Private Selection
Antti Koskela, Rachel Redberg, Yu-Xiang Wang
Private and Federated Stochastic Convex Optimization: Efficient Strategies for Centralized Systems
Roie Reshef, Kfir Levy
Private Gradient Descent for Linear Regression: Tighter Error Bounds and Instance-Specific Uncertainty Estimation
Gavin Brown, Krishnamurthy Dvijotham, Georgina Evans et al.
Private Heterogeneous Federated Learning Without a Trusted Server Revisited: Error-Optimal and Communication-Efficient Algorithms for Convex Losses
Changyu Gao, Andrew Lowy, Xingyu Zhou et al.
Privately Aligning Language Models with Reinforcement Learning
Fan Wu, Huseyin Inan, Arturs Backurs et al.
Privately Learning Smooth Distributions on the Hypercube by Projections
Clément Lalanne, Sébastien Gadat
Private Truly-Everlasting Robust-Prediction
Uri Stemmer
Private Vector Mean Estimation in the Shuffle Model: Optimal Rates Require Many Messages
Hilal Asi, Vitaly Feldman, Jelani Nelson et al.