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Large language models (LLMs) are popular around the world due to their powerful understanding capabilities. As the core component of LLMs, accelerating Transformer through parallelization has gradually become a hot research topic. Mask…

机器学习 · 计算机科学 2026-05-29 Wenhao Dai , Haodong Deng , Mengfei Rong , Xinyu Yang , Hongyu Liu , Fangxin Liu , Hailong Yang , Qianwen Cao , Qingxiao Sun

Text style transfer aims to paraphrase a sentence in one style into another style while preserving content. Due to lack of parallel training data, state-of-art methods are unsupervised and rely on large datasets that share content.…

计算与语言 · 计算机科学 2020-04-27 Xiwen Chen , Kenny Q. Zhu

Due to the massive number of devices in the M2M communication era, new challenges have been brought to the existing random-access (RA) mechanism, such as severe preamble collisions and resource block (RB) wastes. To address these problems,…

信息论 · 计算机科学 2019-10-09 Zhaoji Zhang , Ying Li , Lei Liu , Huimei Han

In this paper, we propose a simple but effective message passing method to improve the boundary quality for the semantic segmentation result. Inspired by the generated sharp edges of superpixel blocks, we employ superpixel to guide the…

计算机视觉与模式识别 · 计算机科学 2021-12-06 Jie Zhu , Huabin Huang , Banghuai Li , Yong Liu , Leye Wang

Distributed computing excels at processing large scale data, but the communication cost for synchronizing the shared parameters may slow down the overall performance. Fortunately, the interactions between parameter and data in many problems…

分布式、并行与集群计算 · 计算机科学 2015-05-19 Mu Li , Dave G. Andersen , Alexander J. Smola

Accelerators, like GPUs, have become a trend to deliver future performance desire, and sharing the same virtual memory space between CPUs and GPUs is increasingly adopted to simplify programming. However, address translation, which is the…

硬件体系结构 · 计算机科学 2021-10-19 Chao Yu , Yuebin Bai , Rui Wang

Network traffic includes data transmitted across a network, such as web browsing and file transfers, and is organized into packets (small units of data) and flows (sequences of packets exchanged between two endpoints). Classifying encrypted…

密码学与安全 · 计算机科学 2024-12-23 Xu-Yang Chen , Lu Han , De-Chuan Zhan , Han-Jia Ye

This paper considers the MapReduce-like coded distributed computing framework originally proposed by Li et al., which uses coding techniques when distributed computing servers exchange their computed intermediate values, in order to reduce…

信息论 · 计算机科学 2020-04-10 Kai Wan , Mingyue Ji , Giuseppe Caire

Far-field microwave power transfer (MPT) will free wireless sensors and other mobile devices from the constraints imposed by finite battery capacities. Integrating MPT with wireless communications to support simultaneous information and…

信息论 · 计算机科学 2015-06-12 Kaibin Huang , Erik G. Larsson

We show that many classical optimization problems --- such as $(1\pm\epsilon)$-approximate maximum flow, shortest path, and transshipment --- can be computed in $\newcommand{\tmix}{{\tau_{\text{mix}}}}\tmix(G)\cdot n^{o(1)}$ rounds of…

数据结构与算法 · 计算机科学 2018-05-29 Mohsen Ghaffari , Jason Li

Hybrid light fidelity (LiFi) and wireless fidelity (WiFi) networks are a promising paradigm of heterogeneous network (HetNet), attributed to the complementary physical properties of optical spectra and radio frequency. However, the current…

机器学习 · 计算机科学 2025-09-09 Han Ji , Xiping Wu , Zhihong Zeng , Chen Chen

Text detection, the key technology for understanding scene text, has become an attractive research topic. For detecting various scene texts, researchers propose plenty of detectors with different advantages: detection-based models enjoy…

计算机视觉与模式识别 · 计算机科学 2022-01-25 Chuang Yang , Mulin Chen , Yuan Yuan , Qi Wang

Massive machine type communication (mMTC) has attracted new coding schemes optimized for reliable short message transmission. In this paper, a novel deep learning-based near-orthogonal superposition (NOS) coding scheme is proposed to…

信息论 · 计算机科学 2022-07-01 Chenghong Bian , Chin-Wei Hsu , Changwoo Lee , Hun-Seok Kim

Edit-based approaches have recently shown promising results on multiple monolingual sequence transduction tasks. In contrast to conventional sequence-to-sequence (Seq2Seq) models, which learn to generate text from scratch as they are…

计算与语言 · 计算机科学 2022-05-11 Kostiantyn Omelianchuk , Vipul Raheja , Oleksandr Skurzhanskyi

Simultaneous machine translation (SMT) takes streaming input utterances and incrementally produces target text. Existing SMT methods mainly use the partial utterance that has already arrived at the input and the generated hypothesis.…

计算与语言 · 计算机科学 2025-06-03 Siqi Ouyang , Oleksii Hrinchuk , Zhehuai Chen , Vitaly Lavrukhin , Jagadeesh Balam , Lei Li , Boris Ginsburg

We present MIST, the Molecular Integration Simulation Toolkit, a lightweight and efficient software library written in C++ which provides an abstract in- terface to common molecular dynamics codes, enabling rapid and portable development of…

The evolution of architectures, programming models, and algorithms is driving communication towards greater asynchrony and concurrency, usually in multithreaded environments. We present LCI, a communication library designed for efficient…

分布式、并行与集群计算 · 计算机科学 2025-08-26 Jiakun Yan , Marc Snir

Contrastive Language-Image Pretraining (CLIP) has achieved remarkable success, leading to rapid advancements in multimodal studies. However, CLIP faces a notable challenge in terms of inefficient data utilization. It relies on a single…

计算机视觉与模式识别 · 计算机科学 2024-06-05 Yu Zhang , Qi Zhang , Zixuan Gong , Yiwei Shi , Yepeng Liu , Duoqian Miao , Yang Liu , Ke Liu , Kun Yi , Wei Fan , Liang Hu , Changwei Wang

The Message-Passing Interface (MPI) and C++ form the backbone of high-performance computing, but MPI only provides C and Fortran bindings. While this offers great language interoperability, high-level programming languages like C++ make…

分布式、并行与集群计算 · 计算机科学 2024-11-13 Tim Niklas Uhl , Matthias Schimek , Lukas Hübner , Demian Hespe , Florian Kurpicz , Christoph Stelz , Peter Sanders

Cross-capability transfer is a key challenge in large language model (LLM) research, with applications in multi-task integration, model compression, and continual learning. Recent works like FuseLLM and FuseChat have demonstrated the…