Papers
Disentangled 3D Scene Generation with Layout Learning
Dave Epstein, Ben Poole, Ben Mildenhall et al.
Disentangled Continual Graph Neural Architecture Search with Invariant Modular Supernet
Zeyang Zhang, Xin Wang, Yijian Qin et al.
Disentangled Graph Self-supervised Learning for Out-of-Distribution Generalization
Haoyang Li, Xin Wang, Zeyang Zhang et al.
Disentanglement Learning via Topology
Nikita Balabin, Daria Voronkova, Ilya Trofimov et al.
Disguised Copyright Infringement of Latent Diffusion Models
Yiwei Lu, Matthew Y. R. Yang, Zuoqiu Liu et al.
Disparate Impact on Group Accuracy of Linearization for Private Inference
Saswat Das, Marco Romanelli, Ferdinando Fioretto
Dissecting Multimodality in VideoQA Transformer Models by Impairing Modality Fusion
Ishaan Singh Rawal, Alexander Matyasko, Shantanu Jaiswal et al.
Distilling Morphology-Conditioned Hypernetworks for Efficient Universal Morphology Control
Zheng Xiong, Risto Vuorio, Jacob Beck et al.
DistiLLM: Towards Streamlined Distillation for Large Language Models
Jongwoo Ko, Sungnyun Kim, Tianyi Chen et al.
Distinguishing the Knowable from the Unknowable with Language Models
Gustaf Ahdritz, Tian Qin, Nikhil Vyas et al.
Distributed Bilevel Optimization with Communication Compression
Yutong He, Jie Hu, Xinmeng Huang et al.
Distributed High-Dimensional Quantile Regression: Estimation Efficiency and Support Recovery
Caixing Wang, Ziliang Shen
Distributional Bellman Operators over Mean Embeddings
Li Kevin Wenliang, Gregoire Deletang, Matthew Aitchison et al.
Distribution Alignment Optimization through Neural Collapse for Long-tailed Classification
Jintong Gao, He Zhao, Dan Dan Guo et al.
Distributionally Robust Data Valuation
Xiaoqiang Lin, Xinyi Xu, Zhaoxuan Wu et al.
DITTO: Diffusion Inference-Time T-Optimization for Music Generation
Zachary Novack, Julian Mcauley, Taylor Berg-Kirkpatrick et al.
Ditto: Quantization-aware Secure Inference of Transformers upon MPC
Haoqi Wu, Wenjing Fang, Yancheng Zheng et al.
Diversified Batch Selection for Training Acceleration
Feng Hong, Yueming Lyu, Jiangchao Yao et al.
Diving into Underwater: Segment Anything Model Guided Underwater Salient Instance Segmentation and A Large-scale Dataset
Shijie Lian, Ziyi Zhang, Hua Li et al.
DMTG: One-Shot Differentiable Multi-Task Grouping
Yuan Gao, Shuguo Jiang, Moran Li et al.
DNA-SE: Towards Deep Neural-Nets Assisted Semiparametric Estimation
Qinshuo Liu, Zixin Wang, Xi’An Li et al.
DNCs Require More Planning Steps
Yara Shamshoum, Nitzan Hodos, Yuval Sieradzki et al.
Do Efficient Transformers Really Save Computation?
Kai Yang, Jan Ackermann, Zhenyu He et al.
Does Label Smoothing Help Deep Partial Label Learning?
Xiuwen Gong, Nitin Bisht, Guandong Xu
DOGE: Domain Reweighting with Generalization Estimation
Simin Fan, Matteo Pagliardini, Martin Jaggi