output
20112026
most citedValley polarization in MoS2 monolayers by optical pumping

3.7k citations

Showing 2024 · cs.LGShow all

10 papers · 2 filters

cs.LG2024★ 3 cited

CSI-BERT2: A BERT-inspired Framework for Efficient CSI Prediction and Classification in Wireless Communication and Sensing

Zijian Zhao, Fanyi Meng, Zhonghao Lyu +3

Channel state information (CSI) is a fundamental component in both wireless communication and sensing systems, enabling critical functions such as radio resource optimization and e…

cs.LG2024

PiLocNet: Physics-informed neural network on 3D localization with rotating point spread function

Mingda Lu, Zitian Ao, Chao Wang +2

For the 3D localization problem using point spread function (PSF) engineering, we propose a novel enhancement of our previously introduced localization neural network, LocNet. The…

cs.LG2024★ 3 cited

Sinc Kolmogorov-Arnold network and its application for solving PDEs with singularities

Tianchi Yu, Jingwei Qiu, Jiang Yang +1

In this paper, we propose to use Sinc interpolation in the context of Kolmogorov-Arnold Networks, neural networks with learnable activation functions, which recently gained attenti…

cs.LG2024★ 3 cited

Fairness-aware Multiobjective Evolutionary Learning

Qingquan Zhang, Jialin Liu, Xin Yao

Multiobjective evolutionary learning (MOEL) has demonstrated its advantages of training fairer machine learning models considering a predefined set of conflicting objectives, inclu…

cs.LG2024★ 3 cited

Spectral Informed Neural Network: An Efficient and Low-Memory PINN

Tianchi Yu, Yiming Qi, Ivan Oseledets +1

With growing investigations into solving partial differential equations by physics-informed neural networks (PINNs), more accurate and efficient PINNs are required to meet the prac…

cs.LG2024

LLM-Barber: Block-Aware Rebuilder for Sparsity Mask in One-Shot for Large Language Models

Yupeng Su, Ziyi Guan, Xiaoqun Liu +6

Large language models (LLMs) have seen substantial growth, necessitating efficient model pruning techniques. Existing post-training pruning methods primarily measure weight importa…

cs.LG2024★ 4 cited

Procedural Fairness in Machine Learning

Ziming Wang, Changwu Huang, Ke Tang +1

Fairness in machine learning (ML) has garnered significant attention. However, current research has mainly concentrated on the distributive fairness of ML models, with limited focu…

cs.LG2024★ 6 cited

TrafPS: A Shapley-based Visual Analytics Approach to Interpret Traffic

Zezheng Feng, Yifan Jiang, Hongjun Wang +5

Recent achievements in deep learning (DL) have shown its potential for predicting traffic flows. Such predictions are beneficial for understanding the situation and making decision…

cs.LG2024★ 26 cited

APTQ: Attention-aware Post-Training Mixed-Precision Quantization for Large Language Models

Ziyi Guan, Hantao Huang, Yupeng Su +3

Large Language Models (LLMs) have greatly advanced the natural language processing paradigm. However, the high computational load and huge model sizes pose a grand challenge for de…

cs.LG2024★ 3 cited

Online Test-Time Adaptation of Spatial-Temporal Traffic Flow Forecasting

Pengxin Guo, Pengrong Jin, Ziyue Li +2

Accurate spatial-temporal traffic flow forecasting is crucial in aiding traffic managers in implementing control measures and assisting drivers in selecting optimal travel routes.…