22 citations · 40 across the 7 of their papers we have counts for
10 papers
LLM4Impact: Integrating Heterogeneous Information for Scientific Impact Prediction
Yong Cao, Markus Flicke, Haoyu He +2
Predicting the future impact of a newly published paper is challenging because it must be inferred from heterogeneous evidence available at publication time. Existing approaches of…
PlanT 2.0: Exposing Biases and Structural Flaws in Closed-Loop Driving
Simon Gerstenecker, Andreas Geiger, Katrin Renz
Most recent work in autonomous driving has prioritized benchmark performance and methodological innovation over in-depth analysis of model failures, biases, and shortcut learning.…
MDPO: Overcoming the Training-Inference Divide of Masked Diffusion Language Models
Haoyu He, Katrin Renz, Yong Cao +1
Diffusion language models, as a promising alternative to traditional autoregressive (AR) models, enable faster generation and richer conditioning on bidirectional context. However,…
DriveLM: Driving with Graph Visual Question Answering
Chonghao Sima, Katrin Renz, Kashyap Chitta +7
We study how vision-language models (VLMs) trained on web-scale data can be integrated into end-to-end driving systems to boost generalization and enable interactivity with human u…
On Offline Evaluation of 3D Object Detection for Autonomous Driving
Tim Schreier, Katrin Renz, Andreas Geiger +1
Prior work in 3D object detection evaluates models using offline metrics like average precision since closed-loop online evaluation on the downstream driving task is costly. Howeve…
PlanT: Explainable Planning Transformers via Object-Level Representations
Katrin Renz, Kashyap Chitta, Otniel-Bogdan Mercea +3
Planning an optimal route in a complex environment requires efficient reasoning about the surrounding scene. While human drivers prioritize important objects and ignore details not…
TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving
Kashyap Chitta, Aditya Prakash, Bernhard Jaeger +3
How should we integrate representations from complementary sensors for autonomous driving? Geometry-based fusion has shown promise for perception (e.g. object detection, motion for…
KING: Generating Safety-Critical Driving Scenarios for Robust Imitation via Kinematics Gradients
Niklas Hanselmann, Katrin Renz, Kashyap Chitta +2
Simulators offer the possibility of safe, low-cost development of self-driving systems. However, current driving simulators exhibit naïve behavior models for background traffic. Ha…
Sign Segmentation with Changepoint-Modulated Pseudo-Labelling
Katrin Renz, Nicolaj C. Stache, Neil Fox +2
The objective of this work is to find temporal boundaries between signs in continuous sign language. Motivated by the paucity of annotation available for this task, we propose a si…
Sign language segmentation with temporal convolutional networks
Katrin Renz, Nicolaj C. Stache, Samuel Albanie +1
The objective of this work is to determine the location of temporal boundaries between signs in continuous sign language videos. Our approach employs 3D convolutional neural networ…