Transformer Based

Transformer-based models are revolutionizing various fields by leveraging self-attention mechanisms to capture long-range dependencies in sequential data, achieving state-of-the-art results in tasks ranging from natural language processing and image recognition to time series forecasting and robotic control. Current research focuses on improving efficiency (e.g., through quantization and optimized architectures), enhancing generalization capabilities, and addressing challenges like handling long sequences and endogeneity. These advancements are significantly impacting diverse scientific communities and practical applications, leading to more accurate, efficient, and robust models across numerous domains.

Papers

December 2, 2022

Transformer-Based Learned Optimization
Erik Gärtner, Luke Metz, Mykhaylo Andriluka, C. Daniel Freeman, Cristian Sminchisescu
Transformer Based Optimization Purpose Optimization Algorithm Efficient Optimization Optimization Method Superior Optimizer

November 30, 2022

November 28, 2022

Summer: WeChat Neural Machine Translation Systems for the WMT22 Biomedical Translation Task
Ernan Li, Fandong Meng, Jie Zhou
Transformer Based Transformer Architecture Translation Task Weibo Dataset

November 26, 2022

November 25, 2022

November 22, 2022

Transformer Based Multi-Grained Features for Unsupervised Person Re-Identification
Jiachen Li, Menglin Wang, Xiaojin Gong
Transformer Based Person Re Identification Feature Wise Unsupervised Re Id

November 20, 2022

Machine Learning Methods for Anomaly Detection in Nuclear Power Plant Power Transformers
Iurii Katser, Dmitriy Raspopov, Vyacheslav Kozitsin, Maxim Mezhov
Machine Learning Anomaly Detection Transformer Based Gas Concentration Power Transformer

November 19, 2022

TORE: Token Reduction for Efficient Human Mesh Recovery with Transformer
Zhiyang Dou, Qingxuan Wu, Cheng Lin, Zeyu Cao, Qiangqiang Wu, Weilin Wan, Taku Komura, Wenping Wang
Transformer Based Human Mesh Recovery Image Token Transformer Based Structure Token Reduction Hand Mesh Recovery

November 18, 2022

November 17, 2022

On the Effect of Pre-training for Transformer in Different Modality on Offline Reinforcement Learning
Shiro Takagi
Fine Tuning Transformer Based Offline Reinforcement Learning Mixed Effect Transformer Based Model Meaningful Representation Pre Trained Transformer Different Modality

November 15, 2022

November 12, 2022

Integrating Transformer and Autoencoder Techniques with Spectral Graph Algorithms for the Prediction of Scarcely Labeled Molecular Data
Nicole Hayes, Ekaterina Merkurjev, Guo-Wei Wei
Transfer Learning Transformer Based Human Prediction Graph Based Numerical Experiment Autoencoder Based Molecular Data Spectral Graph Residue Number

November 11, 2022

Efficient HLA imputation from sequential SNPs data by Transformer
Kaho Tanaka, Kosuke Kato, Naoki Nonaka, Jun Seita
Transformer Based Various Imputation

Transformer Based

Papers

Transformer-Based Learned Optimization

Misogyny classification of German newspaper forum comments

ShaDocNet: Learning Spatial-Aware Tokens in Transformer for Document Shadow Removal

Summer: WeChat Neural Machine Translation Systems for the WMT22 Biomedical Translation Task

How Crucial is Transformer in Decision Transformer?

PatchGT: Transformer over Non-trainable Clusters for Learning Graph Representations

The Naughtyformer: A Transformer Understands Offensive Humor

MUSTER: A Multi-scale Transformer-based Decoder for Semantic Segmentation

Transformer Based Multi-Grained Features for Unsupervised Person Re-Identification

Machine Learning Methods for Anomaly Detection in Nuclear Power Plant Power Transformers

TORE: Token Reduction for Efficient Human Mesh Recovery with Transformer

A Transformer Framework for Data Fusion and Multi-Task Learning in Smart Cities

GPS++: An Optimised Hybrid MPNN/Transformer for Molecular Property Prediction

Delving into Transformer for Incremental Semantic Segmentation

Vision Transformers in Medical Imaging: A Review

On the Effect of Pre-training for Transformer in Different Modality on Offline Reinforcement Learning

ConvFormer: Combining CNN and Transformer for Medical Image Segmentation

Adaptive Multi-Neighborhood Attention based Transformer for Graph Representation Learning

Integrating Transformer and Autoencoder Techniques with Spectral Graph Algorithms for the Prediction of Scarcely Labeled Molecular Data

Efficient HLA imputation from sequential SNPs data by Transformer