Papers
Dissecting Submission Limit in Desk-Rejections: A Mathematical Analysis of Fairness in AI Conference Policies
Yuefan Cao, Xiaoyu Li, Yingyu Liang et al.
Dissecting the Impact of Model Misspecification in Data-Driven Optimization
Adam N. Elmachtoub, Henry Lam, Haixiang Lan et al.
Diss-l-ECT: Dissecting Graph Data with Local Euler Characteristic Transforms
Julius von Rohrscheidt, Bastian Rieck
DiST-4D: Disentangled Spatiotemporal Diffusion with Metric Depth for 4D Driving Scene Generation
Jiazhe Guo, Yikang Ding, Xiwu Chen et al.
DistaLs: a Comprehensive Collection of Language Distance Measures
Rob Van Der Goot, Esther Ploeger, Verena Blaschke et al.
Distance-Adaptive Quaternion Knowledge Graph Embedding with Bidirectional Rotation
Weihua Wang, Qiuyu Liang, Feilong Bao et al.
Distance-Based Tree-Sliced Wasserstein Distance
Hoang V. Tran, Minh-Khoi Nguyen-Nhat, Huyen Trang Pham et al.
Distance between Relevant Information Pieces Causes Bias in Long-Context LLMs
Runchu Tian, Yanghao Li, Yuepeng Fu et al.
Distance Estimation for High-Dimensional Discrete Distributions
Kuldeep S. Meel, Gunjan Kumar, Yash Pote
Distance Preservation Games
Haris Aziz, Hau Chan, Patrick Lederer et al.
Distances Between Top-Truncated Elections of Different Sizes
Piotr Faliszewski, Jitka Mertlová, Pierre Nunn et al.
DISTA-Net: Dynamic Closely-Spaced Infrared Small Target Unmixing
Shengdong Han, Shangdong Yang, Yuxuan Li et al.
DISTIL: Data-Free Inversion of Suspicious Trojan Inputs via Latent Diffusion
Hossein Mirzaei, Zeinab Taghavi, Sepehr Rezaee et al.
Distillation of Diffusion Features for Semantic Correspondence
Frank Fundel, Johannes Schusterbauer, Vincent Tao Hu et al.
Distillation of Discrete Diffusion through Dimensional Correlations
Satoshi Hayakawa, Yuhta Takida, Masaaki Imaizumi et al.
Distillation Scaling Laws
Dan Busbridge, Amitis Shidani, Floris Weers et al.
Distillation versus Contrastive Learning: How to Train Your Rerankers
Zhichao Xu, Zhiqi Huang, Shengyao Zhuang et al.
Distillation versus Contrastive Learning: How to Train Your Rerankers
Zhichao Xu, Zhiqi Huang, Shengyao Zhuang et al.
Distill-C: Enhanced NL2SQL via Distilled Customization with LLMs
Cong Duy Vu Hoang, Gioacchino Tangari, Clemence Lanfranchi et al.
DistillDrive: End-to-End Multi-Mode Autonomous Driving Distillation by Isomorphic Hetero-Source Planning Model
Rui Yu, Xianghang Zhang, Runkai Zhao et al.
Distilled Decoding 1: One-step Sampling of Image Auto-regressive Models with Flow Matching
Enshu Liu, Xuefei Ning, Yu Wang et al.
Distilled Prompt Learning for Incomplete Multimodal Survival Prediction
Yingxue Xu, Fengtao Zhou, Chenyu Zhao et al.
DistillHGNN: A Knowledge Distillation Approach for High-Speed Hypergraph Neural Networks
Saman Forouzandeh, Parham Moradi DW, Mahdi Jalili
Distilling Aggregated Knowledge for Weakly-Supervised Video Anomaly Detection
Jash Dalvi, Ali Dabouei, Gunjan Dhanuka et al.
Distilling an End-to-End Voice Assistant Without Instruction Training Data
William Held, Yanzhe Zhang, Minzhi Li et al.