End to End

"End-to-end" systems aim to streamline complex processes by integrating multiple stages into a single, unified model, eliminating the need for intermediate steps and potentially improving efficiency and performance. Current research focuses on applying this approach across diverse fields, utilizing architectures like transformers, reinforcement learning, and spiking neural networks to tackle challenges in autonomous driving, robotics, speech processing, and natural language processing. This approach offers significant potential for improving the accuracy, speed, and robustness of various applications, while also simplifying development and deployment.

Papers

December 2, 2022

COmic: Convolutional Kernel Networks for Interpretable End-to-End Learning on (Multi-)Omics Data
Jonas C. Ditz, Bernhard Reuter, Nico Pfeifer
End to End Multi Omics Data Comic Analysis Transition Kernel

December 1, 2022

PIZZA: A new benchmark for complex end-to-end task-oriented parsing
Konstantine Arkoudas, Nicolas Guenon des Mesnards, Melanie Rubino, Sandesh Swamy, Saarthak Khanna, Weiqi Sun, Khan Haidar
New Benchmark End to End High Quality Representation Executable Dataset

November 25, 2022

DATE: Dual Assignment for End-to-End Fully Convolutional Object Detection
Yiqun Chen, Qiang Chen, Qinghao Hu, Jian Cheng
End to End Object Detection Deep Convolutional Neural Network Model Convergence CNN Based Detector Design Automation Matching Strategy Resource Exchange

November 22, 2022

Computer Vision for Transit Travel Time Prediction: An End-to-End Framework Using Roadside Urban Imagery
Awad Abdelhalim, Jinhua Zhao
Computer Vision End to End Travel Time Estimation Roadside Camera

November 21, 2022

November 19, 2022

Peeling the Onion: Hierarchical Reduction of Data Redundancy for Efficient Vision Transformer Training
Zhenglun Kong, Haoyu Ma, Geng Yuan, Mengshu Sun, Yanyue Xie, Peiyan Dong, Xin Meng, Xuan Shen, Hao Tang, Minghai Qin, Tianlong Chen, Xiaolong Ma, Xiaohui Xie, Zhangyang Wang, Yanzhi Wang
Vision Transformer End to End Sparse View Information Redundancy Model Reduction Training Datasets

November 17, 2022

Unsupervised Model-based speaker adaptation of end-to-end lattice-free MMI model for speech recognition
Xurong Xie, Xunying Liu, Hui Chen, Hongan Wang
Automatic Speech Recognition Speech Recognition End to End Unsupervised Setting Speaker Adaptation End 2 End Speaker Variability Lattice Free MMI

November 12, 2022

November 8, 2022

Toward Adaptive Semantic Communications: Efficient Data Transmission via Online Learned Nonlinear Transform Source-Channel Coding
Jincheng Dai, Sixian Wang, Ke Yang, Kailin Tan, Xiaoqi Qin, Zhongwei Si, Kai Niu, Ping Zhang
End to End Low Density Parity Check Codec Model Source Channel Coding Memory Efficient Adaptation Aware Communication Nonlinear Transform Efficient Transmission

November 7, 2022

Reranking Overgenerated Responses for End-to-End Task-Oriented Dialogue Systems
Songbo Hu, Ivan Vulić, Fangyu Liu, Anna Korhonen
End to End Dialogue System High Quality Task Oriented Task Oriented Dialogue System Dialogue History Response Generation Model Response Quality

November 3, 2022

PolyBuilding: Polygon Transformer for End-to-End Building Extraction
Yuan Hu, Zhibin Wang, Zhou Huang, Yu Liu
End to End Encoder Decoder Aware Transformer Building Extraction Modular Architecture X Corner Polygonal Building Predictive Representation

November 2, 2022

November 1, 2022

Unified End-to-End Speech Recognition and Endpointing for Fast and Efficient Speech Systems
Shaan Bijwadia, Shuo-yiin Chang, Bo Li, Tara Sainath, Chao Zhang, Yanzhang He
Automatic Speech Recognition End to End Speech System Endpoint Detection

October 31, 2022

October 30, 2022

End to End

Papers

COmic: Convolutional Kernel Networks for Interpretable End-to-End Learning on (Multi-)Omics Data

PIZZA: A new benchmark for complex end-to-end task-oriented parsing

DATE: Dual Assignment for End-to-End Fully Convolutional Object Detection

Computer Vision for Transit Travel Time Prediction: An End-to-End Framework Using Roadside Urban Imagery

SpeechNet: Weakly Supervised, End-to-End Speech Recognition at Industrial Scale

EHSNet: End-to-End Holistic Learning Network for Large-Size Remote Sensing Image Semantic Segmentation

Peeling the Onion: Hierarchical Reduction of Data Redundancy for Efficient Vision Transformer Training

Unsupervised Model-based speaker adaptation of end-to-end lattice-free MMI model for speech recognition

DEYO: DETR with YOLO for Step-by-Step Object Detection

End-to-End Machine Learning Framework for Facial AU Detection in Intensive Care Units

Toward Adaptive Semantic Communications: Efficient Data Transmission via Online Learned Nonlinear Transform Source-Channel Coding

Reranking Overgenerated Responses for End-to-End Task-Oriented Dialogue Systems

PolyBuilding: Polygon Transformer for End-to-End Building Extraction

Fast-U2++: Fast and Accurate End-to-End Speech Recognition in Joint CTC/Attention Frames

BECTRA: Transducer-based End-to-End ASR with BERT-Enhanced Encoder

Unified End-to-End Speech Recognition and Endpointing for Fast and Efficient Speech Systems

Towards Developing State-of-the-Art TTS Synthesisers for 13 Indian Languages with Signal Processing aided Alignments

Modular Hybrid Autoregressive Transducer

XMD: An End-to-End Framework for Interactive Explanation-Based Debugging of NLP Models

Atlas: Automate Online Service Configuration in Network Slicing