4 papers
Closed-Loop Aware Planning via Imitation-Free Speed Scoring for End-to-End Autonomous Driving
Emad Aghajanzadeh, Thomas Schwarzfischer, Marc Kaufeld +8
End-to-end autonomous driving has predominantly relied on open-loop imitation learning for training, which presents two limitations. First, expert demonstrations show only one beha…
Comfortably Stuck: Evaluation Pitfalls in Bench2Drive's Closed-Loop Protocol
Thomas Schwarzfischer, Emad Aghajanzadeh, Moritz Thoma +5
Closed-loop evaluation is widely regarded as a more faithful way to assess end-to-end (E2E) driving models than open-loop evaluation, and Bench2Drive, built on the CARLA simulator,…
Mind the Approximation: Fisher-Weighted SVD Compression for ViTs
Moritz Thoma, Maximilian Groezinger, Maximilian Forstenhäusler +7
Model compression is key to mitigate deployment challenges of ever growing machine learning models. In this area of research, singular value decomposition (SVD)-based compression o…
HiFi-LLP: High-Fidelity, Low-Cost Latency Predictors with Confidence for Robust HW-NAS
Shambhavi Balamuthu Sampath, Behzad Shomali, Nael Fasfous +7
With deep neural networks (DNNs) increasingly deployed on edge devices, hardware (HW)-aware optimization techniques--such as HW-aware compression and HW-aware neural architecture s…