activity
20232025
most citedPaparazzi: A Deep Dive into the Capabilities of Language and Vision Models for Grounding Viewpoint Descriptions

1 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2025

Efficient Scientific Full Text Classification: The Case of EICAT Impact Assessments

Marc Felix Brinner, Sina Zarrieß

This study explores strategies for efficiently classifying scientific full texts using both small, BERT-based models and local large language models like Llama-3.1 8B. We focus on…

cs.CL20251 cited

Mining for Species, Locations, Habitats, and Ecosystems from Scientific Papers in Invasion Biology: A Large-Scale Exploratory Study with Large Language Models

Jennifer D'Souza, Zachary Laubach, Tarek Al Mustafa +3

This paper presents an exploratory study that harnesses the capabilities of large language models (LLMs) to mine key ecological entities from invasion biology literature. Specifica…

cs.CL2025

Implicit Causality-biases in humans and LLMs as a tool for benchmarking LLM discourse capabilities

Florian Kankowski, Torgrim Solstad, Sina Zarriess +1

In this paper, we compare data generated with mono- and multilingual LLMs spanning a range of model sizes with data provided by human participants in an experimental setting invest…

cs.CL2024

GerPS-Compare: Comparing NER methods for legal norm analysis

Sarah T. Bachinger, Christoph Unger, Robin Erd +4

We apply NER to a particular sub-genre of legal texts in German: the genre of legal norms regulating administrative processes in public service administration. The analysis of such…

cs.CV20231 cited

Paparazzi: A Deep Dive into the Capabilities of Language and Vision Models for Grounding Viewpoint Descriptions

Henrik Voigt, Jan Hombeck, Monique Meuschke +2

Existing language and vision models achieve impressive performance in image-text understanding. Yet, it is an open question to what extent they can be used for language understandi…