Papers
Devil is in the Details: Density Guidance for Detail-Aware Generation with Flow Models
Rafal Karczewski, Markus Heinonen, Vikas K Garg
DexScale: Automating Data Scaling for Sim2Real Generalizable Robot Control
Guiliang Liu, Yueci Deng, Runyi Zhao et al.
D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples
Zijing Hu, Fengda Zhang, Kun Kuang
Diagonal Symmetrization of Neural Network Solvers for the Many-Electron Schrödinger Equation
Kevin Han Huang, Ni Zhan, Elif Ertekin et al.
Dialogue Without Limits: Constant-Sized KV Caches for Extended Response in LLMs
Ravi Ghadia, Avinash Kumar, Gaurav Jain et al.
DiffAdvMAP: Flexible Diffusion-Based Framework for Generating Natural Unrestricted Adversarial Examples
Zhengzhao Pan, Hua Chen, Xiaogang Zhang
Differentiable Quadratic Optimization For the Maximum Independent Set Problem
Ismail Alkhouri, Cedric Le Denmat, Yingjie Li et al.
Differentiable Solver Search for Fast Diffusion Sampling
Shuai Wang, Zexian Li, Qipeng Zhang et al.
Differentiable Structure Learning with Ancestral Constraints
Taiyu Ban, Changxin Rong, Xiangyu Wang et al.
Differential Coding for Training-Free ANN-to-SNN Conversion
Zihan Huang, Wei Fang, Tong Bu et al.
Differentially Private Analysis for Binary Response Models: Optimality, Estimation, and Inference
Ce Zhang, Yixin Han, Yafei Wang et al.
Differentially Private Boxplots
Kelly Ramsay, Jairo Diaz-Rodriguez
Differentially Private Federated $k$-Means Clustering with Server-Side Data
Jonathan Scott, Christoph H. Lampert, David Saulpic
Differentially Private Space-Efficient Algorithms for Counting Distinct Elements in the Turnstile Model
Rachel Cummings, Alessandro Epasto, Jieming Mao et al.
Differential Privacy Guarantees of Markov Chain Monte Carlo Algorithms
Andrea Bertazzi, Tim Johnston, Gareth O. Roberts et al.
Differential Privacy Under Class Imbalance: Methods and Empirical Insights
Lucas Rosenblatt, Yuliia Lut, Ethan Turok et al.
Diff-MoE: Diffusion Transformer with Time-Aware and Space-Adaptive Experts
Kun Cheng, Xiao He, Lei Yu et al.
DiffMS: Diffusion Generation of Molecules Conditioned on Mass Spectra
Montgomery Bohde, Mrunali Manjrekar, Runzhong Wang et al.
Diffuse Everything: Multimodal Diffusion Models on Arbitrary State Spaces
Kevin Rojas, Yuchen Zhu, Sichen Zhu et al.
Diffusion Adversarial Post-Training for One-Step Video Generation
Shanchuan Lin, Xin Xia, Yuxi Ren et al.
Diffusion-based Adversarial Purification from the Perspective of the Frequency Domain
Gaozheng Pei, Ke Ma, Yingfei Sun et al.
Diffusion Counterfactual Generation with Semantic Abduction
Rajat R Rasal, Avinash Kori, Fabio De Sousa Ribeiro et al.
Diffusion Instruction Tuning
Chen Jin, Ryutaro Tanno, Amrutha Saseendran et al.
Diffusion Models are Secretly Exchangeable: Parallelizing DDPMs via Auto Speculation
Hengyuan Hu, Aniket Das, Dorsa Sadigh et al.
Diffusion models for Gaussian distributions: Exact solutions and Wasserstein errors
Emile Pierret, Bruno Galerne