ICLR Papers
6,124 papers found • Page 77 of 123
X-Drive: Cross-modality Consistent Multi-Sensor Data Synthesis for Driving Scenarios
Yichen Xie, Chenfeng Xu, Chensheng Peng et al.
X-Fi: A Modality-Invariant Foundation Model for Multimodal Human Sensing
Xinyan Chen, Jianfei Yang
xFinder: Large Language Models as Automated Evaluators for Reliable Evaluation
Qingchen Yu, Zifan Zheng, Shichao Song et al.
XLand-100B: A Large-Scale Multi-Task Dataset for In-Context Reinforcement Learning
Alexander Nikulin, Ilya Zisman, Alexey Zemtsov et al.
X-NeMo: Expressive Neural Motion Reenactment via Disentangled Latent Attention
XiaoChen Zhao, Hongyi Xu, Guoxian Song et al.
YOLO-RD: Introducing Relevant and Compact Explicit Knowledge to YOLO by Retriever-Dictionary
Hao-Tang Tsui, Chien-Yao Wang, Hong-Yuan Liao
Youku Dense Caption: A Large-scale Chinese Video Dense Caption Dataset and Benchmarks
Zixuan Xiong, Guangwei Xu, wenkai zhang et al.
You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning
Ayan Sengupta, Siddhant Chaudhary, Tanmoy Chakraborty
You Only Sample Once: Taming One-Step Text-to-Image Synthesis by Self-Cooperative Diffusion GANs
Yihong Luo, Xiaolong Chen, Xinghua Qu et al.
Your Absorbing Discrete Diffusion Secretly Models the Conditional Distributions of Clean Data
Jingyang Ou, Shen Nie, Kaiwen Xue et al.
Your Mixture-of-Experts LLM Is Secretly an Embedding Model for Free
Ziyue Li, Tianyi Zhou
Your Weak LLM is Secretly a Strong Teacher for Alignment
Leitian Tao, Yixuan Li
YouTube-SL-25: A Large-Scale, Open-Domain Multilingual Sign Language Parallel Corpus
Garrett Tanzer, Biao Zhang
ZAPBench: A Benchmark for Whole-Brain Activity Prediction in Zebrafish
Jan-Matthis Lueckmann, Alexander Immer, Alex Chen et al.
Zero-cost Proxy for Adversarial Robustness Evaluation
Yuqi Feng, Yuwei Ou, Jiahao Fan et al.
ZeroDiff: Solidified Visual-semantic Correlation in Zero-Shot Learning
Zihan Ye, Shreyank Gowda, Shiming Chen et al.
Zero-shot forecasting of chaotic systems
Yuanzhao Zhang, William Gilpin
Zero-shot Imputation with Foundation Inference Models for Dynamical Systems
Patrick Seifner, Kostadin Cvejoski, Antonia Körner et al.
Zero-shot Model-based Reinforcement Learning using Large Language Models
Abdelhakim Benechehab, Youssef Attia El Hili, Ambroise Odonnat et al.
Zero-Shot Natural Language Explanations
Fawaz Sammani, Nikos Deligiannis
Zero-Shot Whole-Body Humanoid Control via Behavioral Foundation Models
Andrea Tirinzoni, Ahmed Touati, Jesse Farebrother et al.
Zeroth-Order Fine-Tuning of LLMs with Transferable Static Sparsity
Wentao Guo, Jikai Long, Yimeng Zeng et al.
Zeroth-Order Policy Gradient for Reinforcement Learning from Human Feedback without Reward Inference
Qining Zhang, Lei Ying
ZETA: Leveraging $Z$-order Curves for Efficient Top-$k$ Attention
Qiuhao Zeng, Jierui Huang, Peng Lu et al.
Zigzag Diffusion Sampling: Diffusion Models Can Self-Improve via Self-Reflection
Lichen Bai, Shitong Shao, zikai zhou et al.
ZIP: An Efficient Zeroth-order Prompt Tuning for Black-box Vision-Language Models
Seonghwan Park, Jaehyeon Jeong, Yongjun Kim et al.
ZooProbe: A Data Engine for Evaluating, Exploring, and Evolving Large-scale Training Data for Multimodal LLMs
Yi-Kai Zhang, Shiyin Lu, Qing-Guo Chen et al.
$\alpha$TC-VAE: On the relationship between Disentanglement and Diversity
Cristian Meo, Louis Mahon, Anirudh Goyal et al.
$\infty$-Diff: Infinite Resolution Diffusion with Subsampled Mollified States
Sam Bond-Taylor, Chris G Willcocks
$\mathbb{D}^2$ Pruning: Message Passing for Balancing Diversity & Difficulty in Data Pruning
Adyasha Maharana, Prateek Yadav, Mohit Bansal
$\mathcal{B}$-Coder: Value-Based Deep Reinforcement Learning for Program Synthesis
Zishun Yu, Yunzhe Tao, Liyu Chen et al.
$\pi$2vec: Policy Representation with Successor Features
Gianluca Scarpellini, Ksenia Konyushkova, Claudio Fantacci et al.
$t^3$-Variational Autoencoder: Learning Heavy-tailed Data with Student's t and Power Divergence
Juno Kim, Jaehyuk Kwon, Mincheol Cho et al.
$\texttt{NAISR}$: A 3D Neural Additive Model for Interpretable Shape Representation
Yining Jiao, Carlton ZDANSKI, Julia Kimbell et al.
3D-Aware Hypothesis & Verification for Generalizable Relative Object Pose Estimation
Chen Zhao, Tong Zhang, Mathieu Salzmann
3D Feature Prediction for Masked-AutoEncoder-Based Point Cloud Pretraining
Siming Yan, Yuqi Yang, Yu-Xiao Guo et al.
3D Reconstruction with Generalizable Neural Fields using Scene Priors
Yang Fu, Shalini De Mello, Xueting Li et al.
A 2-Dimensional State Space Layer for Spatial Inductive Bias
Ethan Baron, Itamar Zimerman, Lior Wolf
A Benchmark for Learning to Translate a New Language from One Grammar Book
Garrett Tanzer, Mirac Suzgun, Eline Visser et al.
A Benchmark Study on Calibration
Linwei Tao, Younan Zhu, Haolan Guo et al.
A Black-box Approach for Non-stationary Multi-agent Reinforcement Learning
Haozhe Jiang, Qiwen Cui, Zhihan Xiong et al.
A Branching Decoder for Set Generation
Zixian Huang, Gengyang Xiao, Yu Gu et al.
Abstractors and relational cross-attention: An inductive bias for explicit relational reasoning in Transformers
Awni Altabaa, Taylor Webb, Jonathan Cohen et al.
Accelerated Convergence of Stochastic Heavy Ball Method under Anisotropic Gradient Noise
Rui Pan, Yuxing Liu, Xiaoyu Wang et al.
Accelerated Sampling with Stacked Restricted Boltzmann Machines
Jorge Fernandez-de-Cossio-Diaz, Clément Roussel, Simona Cocco et al.
Accelerating Data Generation for Neural Operators via Krylov Subspace Recycling
Hong Wang, Zhongkai Hao, Jie Wang et al.
Accelerating Distributed Stochastic Optimization via Self-Repellent Random Walks
Jie Hu, Vishwaraj Doshi, Do Young Eun
Accelerating Sinkhorn algorithm with sparse Newton iterations
Xun Tang, Michael Shavlovsky, Holakou Rahmanian et al.
Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks
Puja Trivedi, Mark Heimann, Rushil Anirudh et al.
Accurate Forgetting for Heterogeneous Federated Continual Learning
Abudukelimu Wuerkaixi, Sen Cui, Jingfeng Zhang et al.