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Found 11 papers, 6 papers with code
Spurious Correlations in Machine Learning: A Survey
Machine learning systems are known to be sensitive to spurious correlations between biased features of the inputs (e. g., background, texture, and secondary objects) and the corresponding labels.
LaMPilot: An Open Benchmark Dataset for Autonomous Driving with Language Model Programs
Autonomous driving (AD) has made significant strides in recent years.
A Survey on Multimodal Large Language Models for Autonomous Driving
We first introduce the background of Multimodal Large Language Models (MLLMs), the multimodal models development using LLMs, and the history of autonomous driving.
MACP: Efficient Model Adaptation for Cooperative Perception
We approach this objective by identifying the key challenges of shifting from single-agent to cooperative settings, adapting the model by freezing most of its parameters and adding a few lightweight modules.
Receive, Reason, and React: Drive as You Say with Large Language Models in Autonomous Vehicles
The fusion of human-centric design and artificial intelligence (AI) capabilities has opened up new possibilities for next-generation autonomous vehicles that go beyond transportation.
PIE: Simulating Disease Progression via Progressive Image Editing
Disease progression simulation is a crucial area of research that has significant implications for clinical diagnosis, prognosis, and treatment.
Drive as You Speak: Enabling Human-Like Interaction with Large Language Models in Autonomous Vehicles
The future of autonomous vehicles lies in the convergence of human-centric design and advanced AI capabilities.
Mitigating Transformer Overconfidence via Lipschitz Regularization
Though Transformers have achieved promising results in many computer vision tasks, they tend to be over-confident in predictions, as the standard Dot Product Self-Attention (DPSA) can barely preserve distance for the unbounded input domain.
CEMFormer: Learning to Predict Driver Intentions from In-Cabin and External Cameras via Spatial-Temporal Transformers
Driver intention prediction seeks to anticipate drivers' actions by analyzing their behaviors with respect to surrounding traffic environments.
ViTASD: Robust Vision Transformer Baselines for Autism Spectrum Disorder Facial Diagnosis
Research progress in the field of ASD facial analysis in pediatric patients has been hindered due to a lack of well-established baselines.
Adversarial Examples Generation for Reducing Implicit Gender Bias in Pre-trained Models
The metric will be used to guide the generation of examples from Pre-trained models.
