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

October 11, 2024

FRASA: An End-to-End Reinforcement Learning Agent for Fall Recovery and Stand Up of Humanoid Robots
Clément Gaspard, Marc Duclusaud, Grégoire Passault, Mélodie Daniel, Olivier Ly
Deep Reinforcement Learning End to End Humanoid Robot Multiple Gait Fall Detection

October 9, 2024

TinyLidarNet: 2D LiDAR-based End-to-End Deep Learning Model for F1TENTH Autonomous Racing
Mohammed Misbah Zarrar, Qitao Weng, Bakhbyergyen Yerjan, Ahmet Soyyigit, Heechul Yun
End to End 2 Dimensional Robot Navigation Autonomous Racing TinyML Model 1D Convolutional

October 7, 2024

HE-Drive: Human-Like End-to-End Driving with Vision Language Models
Junming Wang, Xingyu Zhang, Zebin Xing, Songen Gu, Xiaoyang Guo, Yang Hu, Ziying Song, Qian Zhang, Xiaoxiao Long, Wei Yin
Autonomous Driving Vision Language Model End to End Trajectory Planner Trajectory Prediction Error

October 4, 2024

STREAMS: An Assistive Multimodal AI Framework for Empowering Biosignal Based Robotic Controls
Ali Rabiee, Sima Ghafoori, Xiangyu Bai, Sarah Ostadabbas, Reza Abiri
End to End Self Training Robot Control Assistive Robot Multimodal AI Link Stream End Effector Diverse Biosignals

October 3, 2024

October 2, 2024

RLEF: Grounding Code LLMs in Execution Feedback with Reinforcement Learning
Jonas Gehring, Kunhao Zheng, Jade Copet, Vegard Mella, Taco Cohen, Gabriel Synnaeve
Large Language Model Reinforcement Learning End to End Code Synthesis Competitive Programming Execution Based

October 1, 2024

Deep Model Interpretation with Limited Data : A Coreset-based Approach
Hamed Behzadi-Khormouji, José Oramas
End to End DNN Model Limited Data COreset Selection Model Interpretation

September 30, 2024

Controlling sharpness, SNR and SAR for 3D FSE at 7T by end-to-end learning
Peter Dawood, Martin Blaimer, Jürgen Herrler, Patrick Liebig, Simon Weinmüller, Shaihan Malik, Peter M. Jakob, Moritz Zaiss
End to End Signal to Noise Ratio 3d Vqa Image Fidelity Point Spread Function Node Feature Sharpness 3D Shape Sequence

September 29, 2024

September 25, 2024

Incorporating Spatial Cues in Modular Speaker Diarization for Multi-channel Multi-party Meetings
Ruoyu Wang, Shutong Niu, Gaobin Yang, Jun Du, Shuangqing Qian, Tian Gao, Jia Pan
End to End Speaker Diarization Visual Cue

September 24, 2024

Spelling Correction through Rewriting of Non-Autoregressive ASR Lattices
Leonid Velikovich, Christopher Li, Diamantino Caseiro, Shankar Kumar, Pat Rondon, Kandarp Joshi, Xavier Velez
End to End Automatic Speech Recognition Model Spelling Correction Grapheme to Phoneme Non Autoregressive ASR

September 18, 2024

September 17, 2024

THaMES: An End-to-End Tool for Hallucination Mitigation and Evaluation in Large Language Models
Mengfei Liang, Archish Arun, Zekun Wu, Cristian Munoz, Jonathan Lutch, Emre Kazim, Adriano Koshiyama, Philip Treleaven
Global Evaluation Context Learning End to End Retrieval Augmented Generation Text Generation Mitigating Hallucination

September 16, 2024

September 14, 2024

Leveraging Self-Supervised Learning for Speaker Diarization
Jiangyu Han, Federico Landini, Johan Rohdin, Anna Silnova, Mireia Diez, Lukas Burget
Self Supervised Learning End to End Speaker Diarization Neural Diarization WavLM Speech Encoder

End to End

Papers

FRASA: An End-to-End Reinforcement Learning Agent for Fall Recovery and Stand Up of Humanoid Robots

TinyLidarNet: 2D LiDAR-based End-to-End Deep Learning Model for F1TENTH Autonomous Racing

HE-Drive: Human-Like End-to-End Driving with Vision Language Models

STREAMS: An Assistive Multimodal AI Framework for Empowering Biosignal Based Robotic Controls

Leveraging Event Streams with Deep Reinforcement Learning for End-to-End UAV Tracking

End-to-end Driving in High-Interaction Traffic Scenarios with Reinforcement Learning

RLEF: Grounding Code LLMs in Execution Feedback with Reinforcement Learning

Deep Model Interpretation with Limited Data : A Coreset-based Approach

Controlling sharpness, SNR and SAR for 3D FSE at 7T by end-to-end learning

The Duke Humanoid: Design and Control For Energy Efficient Bipedal Locomotion Using Passive Dynamics

OrientedFormer: An End-to-End Transformer-Based Oriented Object Detector in Remote Sensing Images

Incorporating Spatial Cues in Modular Speaker Diarization for Multi-channel Multi-party Meetings

Spelling Correction through Rewriting of Non-Autoregressive ASR Lattices

Unveiling the Black Box: Independent Functional Module Evaluation for Bird's-Eye-View Perception Model

End-to-End Probabilistic Geometry-Guided Regression for 6DoF Object Pose Estimation

THaMES: An End-to-End Tool for Hallucination Mitigation and Evaluation in Large Language Models

Point2Graph: An End-to-end Point Cloud-based 3D Open-Vocabulary Scene Graph for Robot Navigation

Optimizing Dysarthria Wake-Up Word Spotting: An End-to-End Approach for SLT 2024 LRDWWS Challenge

Learning Agile Swimming: An End-to-End Approach without CPGs

Leveraging Self-Supervised Learning for Speaker Diarization