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The rapid progress of large language models (LLMs) has transformed natural language processing, yet the challenge of efficient adaptation remains unresolved. Full fine-tuning achieves strong performance but imposes prohibitive computational…

Quantum Physics · Physics 2025-09-23 Emily Jimin Roh , Hyojun Ahn , Samuel Yen-Chi Chen , Soohyun Park , Joongheon Kim

Extremely large-scale antenna array (ELAA) is a key candidate technology for the sixth generation (6G) mobile networks. Nevertheless, using substantial numbers of antennas to transmit high-frequency signals in ELAA systems significantly…

Signal Processing · Electrical Eng. & Systems 2025-01-23 Mengzhen Liu , Ming Li , Rang Liu , Qian Liu

While post-training compression techniques effectively reduce the memory footprint, latency, and power consumption of Large Language Models (LLMs), they often result in noticeable accuracy degradation and remain limited by hardware and…

Many areas of machine learning and science involve large linear algebra problems, such as eigendecompositions, solving linear systems, computing matrix exponentials, and trace estimation. The matrices involved often have Kronecker,…

Machine Learning · Computer Science 2023-11-30 Andres Potapczynski , Marc Finzi , Geoff Pleiss , Andrew Gordon Wilson

Recent experimental advances have demonstrated technologies capable of supporting scalable quantum computation. A critical next step is how to put those technologies together into a scalable, fault-tolerant system that is also feasible. We…

Dynamic metasurface antennas (DMA) provide a solution to form compact, cost-effective, energy-efficient multiple-input-multiple output (MIMO) arrays. In this paper, we implement a practical hierarchical codebook with a realistic DMA design…

Signal Processing · Electrical Eng. & Systems 2023-05-17 Joseph Carlson , Miguel R. Castellanos , Robert W. Heath

The scaling law of Large Language Models (LLMs) reveals a power-law relationship, showing diminishing return on performance as model scale increases. While training LLMs from scratch is resource-intensive, fine-tuning a pre-trained model…

Computation and Language · Computer Science 2025-05-22 Yiyun Zhou , Chang Yao , Jingyuan Chen

Entity Alignment (EA) is vital for integrating diverse knowledge graph (KG) data, playing a crucial role in data-driven AI applications. Traditional EA methods primarily rely on comparing entity embeddings, but their effectiveness is…

Computation and Language · Computer Science 2024-10-11 Xuhui Jiang , Yinghan Shen , Zhichao Shi , Chengjin Xu , Wei Li , Zixuan Li , Jian Guo , Huawei Shen , Yuanzhuo Wang

Near-field ultra-massive MIMO (U-MIMO) systems provide enhanced spatial resolution but present challenges for channel estimation, particularly when hybrid architectures are employed. Within this framework, dictionary-based channel…

Signal Processing · Electrical Eng. & Systems 2026-04-02 Luca Antonelli , Antonio Alberto D Amico , Luca Sanguinetti

Entity alignment (EA) aims at identifying equivalent entity pairs across different knowledge graphs (KGs) that refer to the same real-world identity. To circumvent the shortage of seed alignments provided for training, recent EA models…

Artificial Intelligence · Computer Science 2025-07-03 Qijie Ding , Jie Yin , Daokun Zhang , Junbin Gao

This paper presents a general technique for the joint Direction-of-Arrival (DoA) and Time-of-Arrival (ToA) estimation in multipath environments. The proposed ultra-wideband technique is based on phase-mode expansions and the use of nearly…

Signal Processing · Electrical Eng. & Systems 2023-04-28 Alejandro Ramírez-Arroyo , Antonio Alex-Amor , Pablo Padilla , Juan F. Valenzuela-Valdés

The Universal Approximation Theorem (UAT) guarantees universal function approximation but does not explain how residual models distribute approximation across layers. We reframe residual networks as a layer-wise approximation process that…

Machine Learning · Computer Science 2026-04-28 Wei Wang , Xiao-Yong Wei , Qing Li

Near-field sensing with extremely large-scale antenna arrays (ELAAs) in practical 6G systems is expected to operate over broad bandwidths, where delay, Doppler, and spatial effects become tightly coupled across frequency. The purpose of…

Signal Processing · Electrical Eng. & Systems 2026-01-01 Tong Wei , Kumar Vijay Mishra , Bhavani Shankar M. R. , Björn Ottersten

Analog beamforming with phased arrays is a promising technique for 5G wireless communication in millimeter wave bands. A beam focuses on a small range of angles of arrival or departure and corresponds to a set of fixed phase shifts across…

Information Theory · Computer Science 2017-05-15 Mingming Cai , J. Nicholas Laneman , Bertrand Hochwald

The Quantum Approximate Optimization Algorithm (QAOA) is one of the most promising candidates for achieving quantum advantage over classical computers. However, existing compilers lack specialized methods for optimizing QAOA circuits. There…

Quantum Physics · Physics 2024-08-19 Yuchen Zhu , Yidong Zhou , Jinglei Cheng , Yuwei Jin , Boxi Li , Siyuan Niu , Zhiding Liang

Extremely large-scale antenna arrays (ELAA) play a critical role in enabling the functionalities of next generation wireless communication systems. However, as the number of antennas increases, ELAA systems face significant bottlenecks,…

Information Theory · Computer Science 2025-02-10 Yanqing Xu , Erik G. Larsson , Eduard A. Jorswieck , Xiao Li , Shi Jin , Tsung-Hui Chang

The extremely short wavelength of terahertz (THz) communications leads to an extended radiative near-field region, in which some canonical far-field assumptions fail. Existing near-field boundary formulations (Fraunhofer distance) for…

Networking and Internet Architecture · Computer Science 2025-11-04 Peng Zhang , Vitaly Petrov , Emil Björnson

Extremely large-scale antenna array (ELAA) is promising as one of the key ingredients for the sixth generation (6G) of wireless communications. The electromagnetic propagation of spherical wavefronts introduces an additional…

Information Theory · Computer Science 2024-03-20 Xu Shi , Xuehan Wang , Jingbo Tan , Jintao Wang

This paper investigates coordinated beamforming using a modular linear array (MLA), composed of a pair of physically separated uniform linear arrays (ULAs), treated as sub-arrays. We focus on how such setups can give rise to near-field…

Signal Processing · Electrical Eng. & Systems 2024-12-05 Alva Kosasih , Özlem Tugfe Demir , Emil Björnson

In many data classification problems, there is no linear relationship between an explanatory and the dependent variables. Instead, there may be ranges of the input variable for which the observed outcome is signficantly more or less likely.…

Machine Learning · Computer Science 2016-04-13 Mallory Sheth , Roy Welsch , Natasha Markuzon