Improved Content Understanding With Effective Use of Multi-task Contrastive Learning

no code implementations • 18 May 2024 • Akanksha Bindal, Sudarshan Ramanujam, Dave Golland, TJ Hazen, Tina Jiang, Fengyu Zhang, Peng Yan

This work provides a robust foundation for vertical teams across LinkedIn to customize and fine-tune the LLM to their specific applications.

Contrastive Learning Multi-Task Learning +1

Multimodal Fusion with Pre-Trained Model Features in Affective Behaviour Analysis In-the-wild

no code implementations • 22 Mar 2024 • Zhuofan Wen, Fengyu Zhang, Siyuan Zhang, Haiyang Sun, Mingyu Xu, Licai Sun, Zheng Lian, Bin Liu, JianHua Tao

Multimodal fusion is a significant method for most multimodal tasks.

LiRank: Industrial Large Scale Ranking Models at LinkedIn

no code implementations • 10 Feb 2024 • Fedor Borisyuk, Mingzhou Zhou, Qingquan Song, Siyu Zhu, Birjodh Tiwana, Ganesh Parameswaran, Siddharth Dangi, Lars Hertel, Qiang Xiao, Xiaochen Hou, Yunbo Ouyang, Aman Gupta, Sheallika Singh, Dan Liu, Hailing Cheng, Lei Le, Jonathan Hung, Sathiya Keerthi, Ruoyan Wang, Fengyu Zhang, Mohit Kothari, Chen Zhu, Daqi Sun, Yun Dai, Xun Luan, Sirou Zhu, Zhiwei Wang, Neil Daftary, Qianqi Shen, Chengming Jiang, Haichao Wei, Maneesh Varshney, Amol Ghoting, Souvik Ghosh

We present LiRank, a large-scale ranking framework at LinkedIn that brings to production state-of-the-art modeling architectures and optimization methods.

Click-Through Rate Prediction Quantization

FsaNet: Frequency Self-attention for Semantic Segmentation

1 code implementation • 28 Nov 2022 • Fengyu Zhang, Ashkan Panahi, Guangjun Gao

By ablation study, we show that low frequency self-attention can achieve very close or better performance relative to full frequency even without retraining the network.

Instance Segmentation Semantic Segmentation