4 papers
Calibrated Sampling-Free Uncertainty Estimation in Bayesian Deep Learning
Tobias Jan Wieczorek, Leon de Andrade, Thomas Möllenhoff +1
Modern deep learning models remain notoriously prone to overconfidence, limiting their reliability in high-stakes applications. Bayesian methods aim to counter this by learning a d…
Evaluating the Impact of Post-Training Quantization on Reliable VQA with Multimodal LLMs
Paul Jonas Kurz, Tobias Jan Wieczorek, Mohamed A. Abdelsalam +2
Multimodal Large Language Models (MLLM) are increasingly deployed in domains where both reliability and efficiency are critical. However, current models remain overconfident, produ…
Variational Visual Question Answering for Uncertainty-Aware Selective Prediction
Tobias Jan Wieczorek, Nathalie Daun, Mohammad Emtiyaz Khan +1
Despite remarkable progress in recent years, Vision Language Models (VLMs) remain prone to overconfidence and hallucinations on tasks such as Visual Question Answering (VQA) and Vi…
A framework for the emergence and analysis of language in social learning agents
Tobias J. Wieczorek, Tatjana Tchumatchenko, Carlos Wert Carvajal +1
Artificial neural networks (ANNs) are increasingly used as research models, but questions remain about their generalizability and representational invariance. Biological neural net…