Papers
11,955 papers found
Prometheus: Inducing Fine-Grained Evaluation Capability in Language Models
Seungone Kim, Jamin Shin, Yejin Cho et al.
PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt Optimization
Xinyuan Wang, Chenxi Li, Zhen Wang et al.
PromptFusion: Decoupling Stability and Plasticity for Continual Learning
Haoran Chen, Zuxuan Wu, Xintong Han et al.
Prompt Gradient Projection for Continual Learning
Jingyang Qiao, zhizhong zhang, Xin Tan et al.
Prompt Learning with Quaternion Networks
Boya Shi, Zhengqin Xu, Shuai Jia et al.
Prompt Risk Control: A Rigorous Framework for Responsible Deployment of Large Language Models
Thomas P Zollo, Todd Morrill, Zhun Deng et al.
PromptTTS 2: Describing and Generating Voices with Text Prompt
Yichong Leng, Zhifang Guo, Kai Shen et al.
Proper Laplacian Representation Learning
Diego Gomez, Michael Bowling, Marlos C. Machado
Protein Discovery with Discrete Walk-Jump Sampling
Nathan C. Frey, Dan Berenberg, Karina Zadorozhny et al.
Protein-ligand binding representation learning from fine-grained interactions
Shikun Feng, Minghao Li, Yinjun Jia et al.
Protein-Ligand Interaction Prior for Binding-aware 3D Molecule Diffusion Models
Zhilin Huang, Ling Yang, Xiangxin Zhou et al.
Protein Multimer Structure Prediction via Prompt Learning
Ziqi Gao, Xiangguo Sun, Zijing Liu et al.
Prototypical Information Bottlenecking and Disentangling for Multimodal Cancer Survival Prediction
Yilan Zhang, Yingxue Xu, Jianqi Chen et al.
Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo
Haque Ishfaq, Qingfeng Lan, Pan Xu et al.
Provable Benefits of Multi-task RL under Non-Markovian Decision Making Processes
Ruiquan Huang, Yuan Cheng, Jing Yang et al.
Provable Compositional Generalization for Object-Centric Learning
Thaddäus Wiedemer, Jack Brady, Alexander Panfilov et al.
Provable Memory Efficient Self-Play Algorithm for Model-free Reinforcement Learning
Na Li, Yuchen Jiao, Hangguan Shan et al.
Provable Offline Preference-Based Reinforcement Learning
Wenhao Zhan, Masatoshi Uehara, Nathan Kallus et al.
Provable Reward-Agnostic Preference-Based Reinforcement Learning
Wenhao Zhan, Masatoshi Uehara, Wen Sun et al.
Provable Robust Watermarking for AI-Generated Text
Xuandong Zhao, Prabhanjan Vijendra Ananth, Lei Li et al.
Provably Efficient CVaR RL in Low-rank MDPs
Yulai Zhao, Wenhao Zhan, Xiaoyan Hu et al.
Provably Efficient Iterated CVaR Reinforcement Learning with Function Approximation and Human Feedback
Yu Chen, Yihan Du, Pihe Hu et al.
Provably Efficient UCB-type Algorithms For Learning Predictive State Representations
Ruiquan Huang, Yingbin Liang, Jing Yang
Provably Optimal Memory Capacity for Modern Hopfield Models: Transformer-Compatible Dense Associative Memories as Spherical Codes
Jerry Yao-Chieh Hu, Dennis Wu, Han Liu
Provably Robust Conformal Prediction with Improved Efficiency
Ge Yan, Yaniv Romano, Tsui-Wei Weng