Intel（英特尔）

Uncovering Bias in Large Vision-Language Models at Scale with Counterfactuals

Phillip Howard, Kathleen C. Fraser, Anahita Bhiwandiwalla, Svetlana Kiritchenko

机构 * Intel Labs（英特尔实验室） ； National Research Council Canada（加拿大国家研究理事会） 纠错

Comments Accepted to NAACL 2025 main track (oral)

Always-Sparse Training by Growing Connections with Guided Stochastic Exploration

Mike Heddes, Narayan Srinivasa, Tony Givargis, Alexandru Nicolau

机构 * Department of Computer Science, University of California, Irvine（加州大学 Irvine 分校计算机科学系） ； Intel Labs（英特尔实验室） 纠错

Comments Published at the 2025 International Joint Conference on Neural Networks (IJCNN)

Graph Reinforcement Learning for QoS-Aware Load Balancing in Open Radio Access Networks

Omid Semiari, Hosein Nikopour, Shilpa Talwar

机构 * Intel Labs（英特尔实验室） 纠错

Comments To be published in the proceedings of the 2025 IEEE International Conference on Communications (ICC), Seventh Workshop on Data Driven Intelligence for Networks and Systems (DDINS)

PatternPaint: Practical Layout Pattern Generation Using Diffusion-Based Inpainting

Guanglei Zhou, Bhargav Korrapati, Gaurav Rajavendra Reddy, Chen-Chia Chang, Jingyu Pan, Jiang Hu, Yiran Chen, Dipto G. Thakurta

机构 * Dept. of Electrical & Computer Engineering, Duke University（杜克大学电气与计算机工程系） ； Intel Corporation（英特尔公司） ； Dept. of Electrical & Computer Engineering, TAMU, College Station（塔拉斯大学电气与计算机工程系） 纠错

Comments DAC 2025 accepted

ThermalGaussian: Thermal 3D Gaussian Splatting

Rongfeng Lu, Hangyu Chen, Zunjie Zhu, Yuhang Qin, Ming Lu, Le Zhang, Chenggang Yan, Anke Xue

机构 * Hangzhou Dianzi University（杭州电子科技大学） ； Intel Labs China（英特尔中国实验室） ； Lishui Institute of Hangzhou Dianzi University（杭州电子科技大学丽水学院） 纠错

Comments 10 pages, 7 figures

Solving Inverse Problems with Score-Based Generative Priors learned from Noisy Data

Asad Aali, Marius Arvinte, Sidharth Kumar, Jonathan I. Tamir

机构 * Chandra Family Department of Electrical and Computer Engineering, The University of Texas at Austin（德克萨斯大学奥斯汀分校电气与计算机工程系） ； Intel Corporation（英特尔公司） 纠错

Journal ref IEEE Asilomar, 2023

VGNC: Reducing the Overfitting of Sparse-view 3DGS via Validation-guided Gaussian Number Control

Lifeng Lin, Rongfeng Lu, Quan Chen, Haofan Ren, Ming Lu, Yaoqi Sun, Chenggang Yan, Anke Xue

机构 * Hangzhou Dianzi University（杭州电子科技大学） ； Intel Labs China（英特尔中国实验室） ； Lishui University（丽水大学） 纠错

Comments 10 pages,8 figures

Accelerating LLM Inference with Flexible N:M Sparsity via A Fully Digital Compute-in-Memory Accelerator

Akshat Ramachandran, Souvik Kundu, Arnab Raha, Shamik Kundu, Deepak K. Mathaikutty, Tushar Krishna

机构 * Georgia Institute of Technology（佐治亚理工学院） ； Intel Labs（英特尔实验室） ； Intel Corporation（英特尔公司） 纠错