Papers
Predicting the Future by Retrieving the Past
Dazhao Du, Tao Han, Song Guo
Closer to Biological Mechanism: Drug-Drug Interaction Prediction from the Perspective of Pharmacophore
Mingliang Dou, Linfeng Wen, Jinyang Xie et al.
DSCF: Dual-Source Counterfactual Fusion for High-Dimensional Combinatorial Interventions
Jitong Dou, Lingrui Luo, Bing Zhu et al.
Constrained Particle Seeking: Solving Diffusion Inverse Problems with Just Forward Passes
Hongkun Dou, Zike Chen, Zeyu Li et al.
Learning Dynamics as Feedback: An Adaptive Entropy Flow Dynamics Framework for Long-tailed Human Action Recognition
Yuan Dong, Zhe Zhao, Liheng Yu et al.
EnViT: Enhancing the Performance of Early-Exit Vision Transformers via Exit-Aware Structured Dropout-Enabled Self-Distillation
Yonghao Dong, Qiang He, Penghong Rui et al.
Accelerating LLM Inference Throughput via Asynchronous KV Cache Prefetching
Yanhao Dong, Yubo Miao, Weinan Li et al.
RAC-DMVC: Reliability-Aware Contrastive Deep Multi-View Clustering Under Multi-Source Noise
Shihao Dong, Yue Liu, Xiaotong Zhou et al.
Sliding-Window Merging for Compacting Patch-Redundant Layers in LLMs
Xuan Ding, Rui Sun, Yunjian Zhang et al.
Learning Time in Static Classifiers
Xi Ding, Lei Wang, Piotr Koniusz et al.
PrefixGPT: Prefix Adder Optimization by a Generative Pre-trained Transformer
Ruogu Ding, Xin Ning, Ulf Schlichtmann et al.
Communication-efficient Multi-Agent Reinforcement Learning with Spatiotemporal Information Hub
Ling Ding, Tianbai Lyu, Zhiliang Bi et al.
TimeMosaic: Temporal Heterogeneity Guided Time Series Forecasting via Adaptive Granularity Patch and Segment-wise Decoding
Kuiye Ding, Fanda Fan, Chunyi Hou et al.
SimDiff: Simpler Yet Better Diffusion Model for Time Series Point Forecasting
Hang Ding, Xue Wang, Tian Zhou et al.
CIP-Net: Continual Interpretable Prototype-based Network
Federico Di Valerio, Michela Proietti, Alessio Ragno et al.
Demystifying Foreground-Background Memorization in Diffusion Models
Jimmy Z. Di, Yiwei Lu, Yaoliang Yu et al.
Neural Tangent Kernels Under Stochastic Data Augmentation
Joshua DeOliveira, Sajal Chakroborty, Walter Gerych et al.
Random Amalgamation of Adapters for Flatter Loss Landscapes: Towards Class-Incremental Learning with Better Stability
Yao Deng, Xiang Xiang, Jiaqi Gui
InfoDecom: Decomposing Information for Defending Against Privacy Leakage in Split Inference
Ruijun Deng, Zhihui Lu, Qiang Duan
Efficiently Seeking Flat Minima for Better Generalization in Fine-Tuning Large Language Models and Beyond
Jiaxin Deng, Qingcheng Zhu, Junbiao Pang et al.
FedSkeleton: Secure Multi-Party Graph Skeleton Construction for Privacy-Preserving Federated Time-Series Forecasting
Henggang Deng, Yuchao Tang, Wenjie Fu et al.
Intervention-Aware Time Series Modeling: Capturing and Evaluating Feature Dependencies
Ibrahim Delibasoglu, Sanjay Chakraborty, Fredrik Heintz et al.
Statistically Robust Sparse High-order Interaction Model
Diptesh Das, Ichiro Takeuchi, Koji Tsuda
Correspondence Coverage Matters for Multi-Modal Dataset Distillation
Zhuohang Dang, Minnan Luo, Chengyou Jia et al.
Veli: Unsupervised Method and Unified Benchmark for Low-Cost Air Quality Sensor Correction
Yahia Dalbah, Marcel Worring, Yen-Chia Hsu