| 2024 | Converting Transformers to Polynomial Form for Secure Inference Over Homomorphic Encryption. | Itamar Zimerman, Moran Baruch, Nir Drucker, Gilad Ezov, Omri Soceanu, Lior Wolf |
| 2024 | Sharp Rates in Dependent Learning Theory: Avoiding Sample Size Deflation for the Square Loss. | Ingvar M. Ziemann, Stephen Tu, George J. Pappas, Nikolai Matni |
| 2024 | Language Models Represent Beliefs of Self and Others. | Wentao Zhu, Zhining Zhang, Yizhou Wang |
| 2024 | CRoFT: Robust Fine-Tuning with Concurrent Optimization for OOD Generalization and Open-Set OOD Detection. | Lin Zhu, Yifeng Yang, Qinying Gu, Xinbing Wang, Chenghu Zhou, Nanyang Ye |
| 2024 | Online Learning in Betting Markets: Profit versus Prediction. | Haiqing Zhu, Alexander Soen, Yun Kuen Cheung, Lexing Xie |
| 2024 | Antibody Design Using a Score-based Diffusion Model Guided by Evolutionary, Physical and Geometric Constraints. | Tian Zhu, Milong Ren, Haicang Zhang |
| 2024 | Toward Availability Attacks in 3D Point Clouds. | Yifan Zhu, Yibo Miao, Yinpeng Dong, Xiao-Shan Gao |
| 2024 | Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model. | Lianghui Zhu, Bencheng Liao, Qian Zhang, Xinlong Wang, Wenyu Liu, Xinggang Wang |
| 2024 | Iterative Data Smoothing: Mitigating Reward Overfitting and Overoptimization in RLHF. | Banghua Zhu, Michael I. Jordan, Jiantao Jiao |
| 2024 | Improving Open-Ended Text Generation via Adaptive Decoding. | Wenhong Zhu, Hongkun Hao, Zhiwei He, Yiming Ai, Rui Wang |
| 2024 | Asymmetry in Low-Rank Adapters of Foundation Models. | Jiacheng Zhu, Kristjan H. Greenewald, Kimia Nadjahi, Haitz Sez de Ocriz Borde, Rickard Brel Gabrielsson, Leshem Choshen, Marzyeh Ghassemi, Mikhail Yurochkin, Justin Solomon |
| 2024 | Towards Efficient Spiking Transformer: a Token Sparsification Framework for Training and Inference Acceleration. | Zhengyang Zhuge, Peisong Wang, Xingting Yao, Jian Cheng |
| 2024 | GPTSwarm: Language Agents as Optimizable Graphs. | Mingchen Zhuge, Wenyi Wang, Louis Kirsch, Francesco Faccio, Dmitrii Khizbullin, Jrgen Schmidhuber |
| 2024 | Generative Active Learning for Long-tailed Instance Segmentation. | Muzhi Zhu, Chengxiang Fan, Hao Chen, Yang Liu, Weian Mao, Xiaogang Xu, Chunhua Shen |
| 2024 | Iterative Search Attribution for Deep Neural Networks. | Zhiyu Zhu, Huaming Chen, Xinyi Wang, Jiayu Zhang, Zhibo Jin, Jason Xue, Jun Shen |
| 2024 | COALA: A Practical and Vision-Centric Federated Learning Platform. | Weiming Zhuang, Jian Xu, Chen Chen, Jingtao Li, Lingjuan Lyu |
| 2024 | Reinformer: Max-Return Sequence Modeling for Offline RL. | Zifeng Zhuang, Dengyun Peng, Jinxin Liu, Ziqi Zhang, Donglin Wang |
| 2024 | Stealthy Imitation: Reward-guided Environment-free Policy Stealing. | Zhixiong Zhuang, Maria-Irina Nicolae, Mario Fritz |
| 2024 | Dynamic Evaluation of Large Language Models by Meta Probing Agents. | Kaijie Zhu, Jindong Wang, Qinlin Zhao, Ruochen Xu, Xing Xie |
| 2024 | Catapults in SGD: spikes in the training loss and their impact on generalization through feature learning. | Libin Zhu, Chaoyue Liu, Adityanarayanan Radhakrishnan, Mikhail Belkin |
| 2024 | Switched Flow Matching: Eliminating Singularities via Switching ODEs. | Qunxi Zhu, Wei Lin |
| 2024 | Model Tailor: Mitigating Catastrophic Forgetting in Multi-modal Large Language Models. | Didi Zhu, Zhongyi Sun, Zexi Li, Tao Shen, Ke Yan, Shouhong Ding, Chao Wu, Kun Kuang |
| 2024 | Score identity Distillation: Exponentially Fast Distillation of Pretrained Diffusion Models for One-Step Generation. | Mingyuan Zhou, Huangjie Zheng, Zhendong Wang, Mingzhang Yin, Hai Huang |
| 2024 | ArCHer: Training Language Model Agents via Hierarchical Multi-Turn RL. | Yifei Zhou, Andrea Zanette, Jiayi Pan, Sergey Levine, Aviral Kumar |
| 2024 | Exploring Training on Heterogeneous Data with Mixture of Low-rank Adapters. | Yuhang Zhou, Zihua Zhao, Siyuan Du, Haolin Li, Jiangchao Yao, Ya Zhang, Yanfeng Wang |