1 citations · 1 across the 4 of their papers we have counts for
4 papers
Towards Dependable Retrieval-Augmented Generation Using Factual Confidence Prediction
Florian Geissler, Francesco Carella, Laura Fieback +1
Incorporating specific knowledge into large language models via retrieval-augmented generation (RAG) is a widespread technique that fuels many of today's industry AI applications.…
Efficient Contrastive Decoding with Probabilistic Hallucination Detection - Mitigating Hallucinations in Large Vision Language Models -
Laura Fieback, Nishilkumar Balar, Jakob Spiegelberg +1
Despite recent advances in Large Vision Language Models (LVLMs), these models still suffer from generating hallucinatory responses that do not align with the visual input provided.…
MetaToken: Detecting Hallucination in Image Descriptions by Meta Classification
Laura Fieback, Jakob Spiegelberg, Hanno Gottschalk
Large Vision Language Models (LVLMs) have shown remarkable capabilities in multimodal tasks like visual question answering or image captioning. However, inconsistencies between the…
Temporal Performance Prediction for Deep Convolutional Long Short-Term Memory Networks
Laura Fieback, Bidya Dash, Jakob Spiegelberg +1
Quantifying predictive uncertainty of deep semantic segmentation networks is essential in safety-critical tasks. In applications like autonomous driving, where video data is availa…