Papers
11,951 papers found
Progressive Parameter Efficient Transfer Learning for Semantic Segmentation
Nan Zhou, Huiqun Wang, Yaoyan Zheng et al.
Progressive Token Length Scaling in Transformer Encoders for Efficient Universal Segmentation
Abhishek Aich, Yumin Suh, Samuel Schulter et al.
Progress or Regress? Self-Improvement Reversal in Post-training
Ting Wu, Xuefeng Li, Pengfei Liu
Projection Head is Secretly an Information Bottleneck
Zhuo Ouyang, Kaiwen Hu, Qi Zhang et al.
Prompt as Knowledge Bank: Boost Vision-language model via Structural Representation for zero-shot medical detection
Yuguang Yang, Tongfei Chen, Haoyu Huang et al.
Prompting Fairness: Integrating Causality to Debias Large Language Models
Jingling Li, Zeyu Tang, Xiaoyu Liu et al.
Promptriever: Instruction-Trained Retrievers Can Be Prompted Like Language Models
Orion Weller, Benjamin Van Durme, Dawn Lawrie et al.
ProtComposer: Compositional Protein Structure Generation with 3D Ellipsoids
Hannes Stark, Bowen Jing, Tomas Geffner et al.
Protecting against simultaneous data poisoning attacks
Neel Alex, Shoaib Ahmed Siddiqui, Amartya Sanyal et al.
Proteina: Scaling Flow-based Protein Structure Generative Models
Tomas Geffner, Kieran Didi, Zuobai Zhang et al.
ProteinBench: A Holistic Evaluation of Protein Foundation Models
Fei YE, Zaixiang Zheng, Dongyu Xue et al.
Protein Language Model Fitness is a Matter of Preference
Cade W Gordon, Amy X. Lu, Pieter Abbeel
ProtoSnap: Prototype Alignment For Cuneiform Signs
Rachel Mikulinsky, Morris Alper, Shai Gordin et al.
Prototype antithesis for biological few-shot class-incremental learning
Binghao Liu, Han Yang, Fang Wan et al.
ProtPainter: Draw or Drag Protein via Topology-guided Diffusion
Zhengxi Lu, Shizhuo Cheng, Tintin Jiang et al.
Provable Benefit of Annealed Langevin Monte Carlo for Non-log-concave Sampling
Wei Guo, Molei Tao, Yongxin Chen
Provable Convergence and Limitations of Geometric Tempering for Langevin Dynamics
Omar Chehab, Anna Korba, Austin J Stromme et al.
Provable Convergence Bounds for Hybrid Dynamical Sampling and Optimization
Matthew X. Burns, Qingyuan Hou, Michael Huang
Provable Robust Overfitting Mitigation in Wasserstein Distributionally Robust Optimization
Shuang Liu, Yihan Wang, Yifan Zhu et al.
Provable Uncertainty Decomposition via Higher-Order Calibration
Gustaf Ahdritz, Aravind Gollakota, Parikshit Gopalan et al.
Provable unlearning in topic modeling and downstream tasks
Stanley Wei, Sadhika Malladi, Sanjeev Arora et al.
Provable weak-to-strong generalization via benign overfitting
David Xing Wu, Anant Sahai
Provably Accurate Shapley Value Estimation via Leverage Score Sampling
Christopher Musco, R. Teal Witter
Provably Reliable Conformal Prediction Sets in the Presence of Data Poisoning
Yan Scholten, Stephan Günnemann
Provably Robust Explainable Graph Neural Networks against Graph Perturbation Attacks
Jiate Li, Meng Pang, Yun Dong et al.