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From the 1 of 14 linked papers with an AI index.

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20242026
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14 papers

eess.SP2026

Computationally Efficient Neural Receivers via Axial Self-Attention

SaiKrishna Saketh Yellapragada, Atchutaram K. Kocharlakota, Mário Costa +2

The paper introduces an axial self‑attention transformer neural receiver that reduces computational complexity while achieving state‑of‑the‑art block error rate performance for wir…

cs.LG2026

Finer Parameter Steps for Low-Rank PEFT: A Controlled Study with CP Tensor Adapters

Xinjue Wang, Xiuheng Wang, Yejun Zhang +3

Low-rank adapters are usually compared by sweeping a small set of ranks, but the rank also fixes the resolution of the parameter budget. For a OPT attention proj…

eess.SP2026

Tensor Train Decomposition Based Noise Reduction and Enhanced Parameter Estimation for FMCW MIMO Radar Systems

Luoyan Zhu, Sergiy A. Vorobyov, Jie Wang +2

Frequency modulated continuous wave (FMCW) radar is widely used in autonomous driving and industrial inspection due to its high-resolution target location and velocity estimation c…

cs.IT2026

Frequency Range 3 for ISAC in 6G: Potentials and Challenges

Gayan Aruma Baduge, Mojtaba Vaezi, Janith K. Dassanayake +3

Spanning 7-24 GHz, frequency range 3 (FR3), is a key enabler for next-generation wireless networks by bridging the coverage of sub-6 GHz and the capacity of millimeter-wave bands.…

cs.IT2026

A Tutorial on AI-Empowered Integrated Sensing and Communications

Mojtaba Vaezi, Gayan Aruma Baduge, Esa Ollila +1

Integrating sensing and communication (ISAC) can help overcome the challenges of limited spectrum and expensive hardware, leading to improved energy and cost efficiency. While full…

eess.IV2026

Anisotropic Tensor Deconvolution of Hyperspectral Images

Xinjue Wang, Xiuheng Wang, Esa Ollila +1

Hyperspectral image (HSI) deconvolution is a challenging ill-posed inverse problem, made difficult by the data's high dimensionality.We propose a parameter-parsimonious framework b…