Papers
Dissecting Query-Key Interaction in Vision Transformers
Xu Pan, Aaron Philip, Ziqian Xie et al.
Dissecting the Failure of Invariant Learning on Graphs
Qixun Wang, Yifei Wang, Yisen Wang et al.
Dissecting the Interplay of Attention Paths in a Statistical Mechanics Theory of Transformers
Lorenzo Tiberi, Francesca Mignacco, Kazuki Irie et al.
DistillNeRF: Perceiving 3D Scenes from Single-Glance Images by Distilling Neural Fields and Foundation Model Features
Letian Wang, Seung Wook Kim, Jiawei Yang et al.
Distributed Least Squares in Small Space via Sketching and Bias Reduction
Sachin Garg, Kevin Tan, Michał Dereziński
Distributed-Order Fractional Graph Operating Network
Kai Zhao, Xuhao Li, Qiyu Kang et al.
Distributionally Robust Performative Prediction
Songkai Xue, Yuekai Sun
Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithms
Miao Lu, Han Zhong, Tong Zhang et al.
Distributional Preference Alignment of LLMs via Optimal Transport
Igor Melnyk, Youssef Mroueh, Brian Belgodere et al.
Distributional regression: CRPS-error bounds for model fitting, model selection and convex aggregation
Clément Dombry, Ahmed Zaoui
Distributional Reinforcement Learning with Regularized Wasserstein Loss
Ke Sun, Yingnan Zhao, Wulong Liu et al.
Distributional Successor Features Enable Zero-Shot Policy Optimization
Chuning Zhu, Xinqi Wang, Tyler Han et al.
Distribution-Aware Data Expansion with Diffusion Models
Haowei Zhu, Ling Yang, Jun-Hai Yong et al.
Distribution Guidance Network for Weakly Supervised Point Cloud Semantic Segmentation
Zhiyi Pan, Wei Gao, Shan Liu et al.
Distribution Learning with Valid Outputs Beyond the Worst-Case
Nick Rittler, Kamalika Chaudhuri
DistrictNet: Decision-aware learning for geographical districting
Cheikh Ahmed, Alexandre Forel, Axel Parmentier et al.
DiTFastAttn: Attention Compression for Diffusion Transformer Models
Zhihang Yuan, Hanling Zhang, Pu Lu et al.
Divergences between Language Models and Human Brains
Yuchen Zhou, Emmy Liu, Graham Neubig et al.
Diversify, Contextualize, and Adapt: Efficient Entropy Modeling for Neural Image Codec
Jun-Hyuk Kim, Seungeon Kim, Won-Hee Lee et al.
Diversity-Driven Synthesis: Enhancing Dataset Distillation through Directed Weight Adjustment
Jiawei Du, Xin Zhang, Juncheng Hu et al.
Diversity Is Not All You Need: Training A Robust Cooperative Agent Needs Specialist Partners
Rujikorn Charakorn, Poramate Manoonpong, Nat Dilokthanakul
Divide-and-Conquer Meets Consensus: Unleashing the Power of Functions in Code Generation
Jingchang Chen, Hongxuan Tang, Zheng Chu et al.
Divide-and-Conquer Posterior Sampling for Denoising Diffusion priors
Yazid Janati, Badr Moufad, Alain Durmus et al.
Divide-and-Conquer Predictive Coding: a structured Bayesian inference algorithm
Eli Sennesh, Hao Wu, Tommaso Salvatori
D-LLM: A Token Adaptive Computing Resource Allocation Strategy for Large Language Models
Yikun Jiang, Huanyu Wang, Lei Xie et al.