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In this paper, we propose the Hierarchical Document Transformer (HDT), a novel sparse Transformer architecture tailored for structured hierarchical documents. Such documents are extremely important in numerous domains, including science,…

Machine Learning · Computer Science 2024-07-12 Haoyu He , Markus Flicke , Jan Buchmann , Iryna Gurevych , Andreas Geiger

Speculative decoding is an effective and lossless approach for accelerating LLM inference. However, existing widely adopted model-based draft designs, such as EAGLE3, improve accuracy at the cost of multi-step autoregressive inference,…

Computation and Language · Computer Science 2026-01-28 Fuliang Liu , Xue Li , Ketai Zhao , Yinxi Gao , Ziyan Zhou , Zhonghui Zhang , Zhibin Wang , Wanchun Dou , Sheng Zhong , Chen Tian

We consider a multidimensional polychromatic radiative transfer (RT) problem, accounting for scattering processes in a general form, i.e. anisotropic (dipole) scattering with partial frequency redistribution. Given a discrete ordinates…

Numerical Analysis · Mathematics 2026-02-26 Pietro Benedusi , Simone Riva , Luca Belluzzi , Stefano Serra-Capizzano

Using Optical Orthogonal Frequency Multiplexing (O-OFDM), variable bandwidth channels can be created in Elastic Optical Networks (EON). This allows the use of spectrum more efficiently by allocating integral multiple of basic bandwidth…

Networking and Internet Architecture · Computer Science 2022-12-09 Varsha Lohani , Anjali Sharma , Yatindra Nath Singh

Diffusion Transformers (DiTs) introduce the transformer architecture to diffusion tasks for latent-space image generation. With an isotropic architecture that chains a series of transformer blocks, DiTs demonstrate competitive performance…

Computer Vision and Pattern Recognition · Computer Science 2024-10-31 Yuchuan Tian , Zhijun Tu , Hanting Chen , Jie Hu , Chao Xu , Yunhe Wang

Dispersion of mobile robots over the nodes of an anonymous graph is an important problem and turns out to be a crucial subroutine for designing efficient algorithms for many fundamental graph problems via mobile robots. In this problem,…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-10-28 Rik Banerjee , Manish Kumar , Anisur Rahaman Molla

We introduce Eff-GRot, an approach for efficient and generalizable rotation estimation from RGB images. Given a query image and a set of reference images with known orientations, our method directly predicts the object's rotation in a…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Fanis Mathioulakis , Gorjan Radevski , Tinne Tuytelaars

Despite recent advances in dexterous manipulations, the manipulation of articulated objects and generalization across different categories remain significant challenges. To address these issues, we introduce DART, a novel framework that…

Robotics · Computer Science 2025-09-19 Hao Zhang , Zhen Kan , Weiwei Shang , Yongduan Song

Cryptography is the study of methods of sending messages in disguised form so that only the intended recipients can remove the disguise and read the messages. Information security has become a very critical aspect of modern communication…

Cryptography and Security · Computer Science 2012-02-10 D. Sravana Kumar , CH. Suneetha , A. Chandrasekhar

Random unitary circuits have become a model system to investigate information scrambling in quantum systems. In the literature, mostly random circuits with Haar-distributed gate operations have been considered. In this work, we investigate…

Quantum Physics · Physics 2025-05-05 Zhiyang Tan , Piet W. Brouwer

Empirical risk minimization (ERM) and distributionally robust optimization (DRO) are popular approaches for solving stochastic optimization problems that appear in operations management and machine learning. Existing generalization error…

Optimization and Control · Mathematics 2023-09-26 Garud Iyengar , Henry Lam , Tianyu Wang

To train machine learning models that are robust to distribution shifts in the data, distributionally robust optimization (DRO) has been proven very effective. However, the existing approaches to learning a distributionally robust model…

Machine Learning · Computer Science 2022-03-21 Farzin Haddadpour , Mohammad Mahdi Kamani , Mehrdad Mahdavi , Amin Karbasi

A group of $n$ users want to run a distributed protocol $\pi$ over a network where communication occurs via private point-to-point channels. Unfortunately, an adversary, who knows $\pi$, is able to maliciously flip bits on the channels. Can…

Cryptography and Security · Computer Science 2017-07-26 Abhinav Aggarwal , Varsha Dani , Thomas P. Hayes , Jared Saia

The performances of the routing protocols are important since they compute the primary path between source and destination. In addition, routing protocols need to detect failure within a short period of time when nodes move to start…

Networking and Internet Architecture · Computer Science 2011-08-09 Radwan abujassar , Mohammed ghanbari

To ensure high availability in large scale distributed systems, Conflict-free Replicated Data Types (CRDTs) relax consistency by allowing immediate query and update operations at the local replica, with no need for remote synchronization.…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-03-12 Vitor Enes , Paulo Sérgio Almeida , Carlos Baquero , João Leitão

Diffusion Policies have demonstrated impressive performance in robotic manipulation tasks. However, their long inference time, resulting from an extensive iterative denoising process, and the need to execute an action chunk before the next…

Robotics · Computer Science 2025-08-08 Yufei Duan , Hang Yin , Danica Kragic

We consider three types of application layer coding for streaming over lossy links: random linear coding, systematic random linear coding, and structured coding. The file being streamed is divided into sub-blocks (generations). Code symbols…

Information Theory · Computer Science 2012-06-15 Yao Li , Péter Vingelmann , Morten Videbæk Pedersen , Emina Soljanin

This letter proposes a sparse diffusion steepest-descent algorithm for one bit compressed sensing in wireless sensor networks. The approach exploits the diffusion strategy from distributed learning in the one bit compressed sensing…

Machine Learning · Statistics 2016-01-05 Hadi Zayyani , Mehdi Korki , Farrokh Marvasti

While traditional Deep Learning (DL) optimization methods treat all training samples equally, Distributionally Robust Optimization (DRO) adaptively assigns importance weights to different samples. However, a significant gap exists between…

Multiple rotation-based transformation (MRBT) was introduced recently for mitigating the apriori-knowledge independent component analysis (AK-ICA) attack on rotation-based transformation (RBT), which is used for privacy-preserving data…

Cryptography and Security · Computer Science 2010-06-11 Dowon Hong , Abedelaziz Mohaisen