| 2024 | Mean Field Langevin Actor-Critic: Faster Convergence and Global Optimality beyond Lazy Learning. | Kakei Yamamoto, Kazusato Oko, Zhuoran Yang, Taiji Suzuki |
| 2024 | FairProof : Confidential and Certifiable Fairness for Neural Networks. | Chhavi Yadav, Amrita Roy Chowdhury, Dan Boneh, Kamalika Chaudhuri |
| 2024 | Sparse Inducing Points in Deep Gaussian Processes: Enhancing Modeling with Denoising Diffusion Variational Inference. | Jian Xu, Delu Zeng, John W. Paisley |
| 2024 | Random Masking Finds Winning Tickets for Parameter Efficient Fine-tuning. | Jing Xu, Jingzhao Zhang |
| 2024 | Exponential Spectral Pursuit: An Effective Initialization Method for Sparse Phase Retrieval. | Mengchu Xu, Yuxuan Zhang, Jian Wang |
| 2024 | Out-of-Distribution Detection via Deep Multi-Comprehension Ensemble. | Chenhui Xu, Fuxun Yu, Zirui Xu, Nathan Inkawhich, Xiang Chen |
| 2024 | SLOG: An Inductive Spectral Graph Neural Network Beyond Polynomial Filter. | Haobo Xu, Yuchen Yan, Dingsu Wang, Zhe Xu, Zhichen Zeng, Tarek F. Abdelzaher, Jiawei Han, Hanghang Tong |
| 2024 | A Sparsity Principle for Partially Observable Causal Representation Learning. | Danru Xu, Dingling Yao, Sbastien Lachapelle, Perouz Taslakian, Julius von Kgelgen, Francesco Locatello, Sara Magliacane |
| 2024 | Learning Exceptional Subgroups by End-to-End Maximizing KL-Divergence. | Sascha Xu, Nils Philipp Walter, Janis Kalofolias, Jilles Vreeken |
| 2024 | Principled Preferential Bayesian Optimization. | Wenjie Xu, Wenbin Wang, Yuning Jiang, Bratislav Svetozarevic, Colin N. Jones |
| 2024 | Pricing with Contextual Elasticity and Heteroscedastic Valuation. | Jianyu Xu, Yu-Xiang Wang |
| 2024 | Adaptive Group Personalization for Federated Mutual Transfer Learning. | Haoqing Xu, Dian Shen, Meng Wang, Beilun Wang |
| 2024 | Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine Translation. | Haoran Xu, Amr Sharaf, Yunmo Chen, Weiting Tan, Lingfeng Shen, Benjamin Van Durme, Kenton Murray, Young Jin Kim |
| 2024 | Prompt-guided Precise Audio Editing with Diffusion Models. | Manjie Xu, Chenxing Li, Duzhen Zhang, Dan Su, Wei Liang, Dong Yu |
| 2024 | Meta-Reinforcement Learning Robust to Distributional Shift Via Performing Lifelong In-Context Learning. | Tengye Xu, Zihao Li, Qinyuan Ren |
| 2024 | Low-Rank Similarity Mining for Multimodal Dataset Distillation. | Yue Xu, Zhilin Lin, Yusong Qiu, Cewu Lu, Yong-Lu Li |
| 2024 | Enhancing Vision Transformer: Amplifying Non-Linearity in Feedforward Network Module. | Yixing Xu, Chao Li, Dong Li, Xiao Sheng, Fan Jiang, Lu Tian, Ashish Sirasao, Emad Barsoum |
| 2024 | Soft Prompt Recovers Compressed LLMs, Transferably. | Zhaozhuo Xu, Zirui Liu, Beidi Chen, Shaochen (Henry) Zhong, Yuxin Tang, Jue Wang, Kaixiong Zhou, Xia Hu, Anshumali Shrivastava |
| 2024 | Robust Inverse Constrained Reinforcement Learning under Model Misspecification. | Sheng Xu, Guiliang Liu |
| 2024 | Conformal prediction for multi-dimensional time series by ellipsoidal sets. | Chen Xu, Hanyang Jiang, Yao Xie |
| 2024 | Equivariant Graph Neural Operator for Modeling 3D Dynamics. | Minkai Xu, Jiaqi Han, Aaron Lou, Jean Kossaifi, Arvind Ramanathan, Kamyar Azizzadenesheli, Jure Leskovec, Stefano Ermon, Anima Anandkumar |
| 2024 | BiSHop: Bi-Directional Cellular Learning for Tabular Data with Generalized Sparse Modern Hopfield Model. | Chenwei Xu, Yu-Chao Huang, Jerry Yao-Chieh Hu, Weijian Li, Ammar Gilani, Hsi-Sheng Goan, Han Liu |
| 2024 | Practical Hamiltonian Monte Carlo on Riemannian Manifolds via Relativity Theory. | Kai Xu, Hong Ge |
| 2024 | Is DPO Superior to PPO for LLM Alignment? A Comprehensive Study. | Shusheng Xu, Wei Fu, Jiaxuan Gao, Wenjie Ye, Weilin Liu, Zhiyu Mei, Guangju Wang, Chao Yu, Yi Wu |
| 2024 | Unifying Bayesian Flow Networks and Diffusion Models through Stochastic Differential Equations. | Kaiwen Xue, Yuhao Zhou, Shen Nie, Xu Min, Xiaolu Zhang, Jun Zhou, Chongxuan Li |