2 citations · 2 across the 7 of their papers we have counts for
8 papers
From Values to Benchmarks: Evaluating Large Language Models for Governmental Use in Dutch
Laurens Samson, Iva Gornishka, Gossa Lô +2
Large language models are increasingly being deployed in governmental settings, yet few existing evaluation frameworks jointly reflect the values of public administration and the l…
Same Content, Different Answers: Cross-Modal Inconsistency in MLLMs
Angela van Sprang, Laurens Samson, Ana Lucic +3
We introduce two new benchmarks REST and REST+ (Render-Equivalence Stress Tests) to enable systematic evaluation of cross-modal inconsistency in multimodal large language models (M…
Segment Any 3D-Part in a Scene from a Sentence
Hongyu Wu, Pengwan Yang, Yuki M. Asano +1
This paper aims to achieve the segmentation of any 3D part in a scene based on natural language descriptions, extending beyond traditional object-level 3D scene understanding and a…
SAMSelect: A Spectral Index Search for Marine Debris Visualization using Segment Anything
Joost van Dalen, Yuki M. Asano, Marc Russwurm
This work proposes SAMSelect, an algorithm to obtain a salient three-channel visualization for multispectral images. We develop SAMSelect and show its use for marine scientists vis…
CROC: Evaluating and Training T2I Metrics with Pseudo- and Human-Labeled Contrastive Robustness Checks
Christoph Leiter, Yuki M. Asano, Margret Keuper +1
The assessment of evaluation metrics (meta-evaluation) is crucial for determining the suitability of existing metrics in text-to-image (T2I) generation tasks. Human-based meta-eval…
Unsupervised Parameter Efficient Source-free Post-pretraining
Abhishek Jha, Tinne Tuytelaars, Yuki M. Asano
Following the success in NLP, the best vision models are now in the billion parameter ranges. Adapting these large models to a target distribution has become computationally and ec…
Foundation Model or Finetune? Evaluation of few-shot semantic segmentation for river pollution
Marga Don, Stijn Pinson, Blanca Guillen Cebrian +1
Foundation models (FMs) are a popular topic of research in AI. Their ability to generalize to new tasks and datasets without retraining or needing an abundance of data makes them a…
The Common Stability Mechanism behind most Self-Supervised Learning Approaches
Abhishek Jha, Matthew B. Blaschko, Yuki M. Asano +1
Last couple of years have witnessed a tremendous progress in self-supervised learning (SSL), the success of which can be attributed to the introduction of useful inductive biases i…