1 citations · 2 across the 8 of their papers we have counts for
5 papers · 1 filter
Enhancing Software-Related Information Extraction via Single-Choice Question Answering with Large Language Models
Wolfgang Otto, Sharmila Upadhyaya, Stefan Dietze
This paper describes our participation in the Shared Task on Software Mentions Disambiguation (SOMD), with a focus on improving relation extraction in scholarly texts through gener…
Dissecting Paraphrases: The Impact of Prompt Syntax and supplementary Information on Knowledge Retrieval from Pretrained Language Models
Stephan Linzbach, Dimitar Dimitrov, Laura Kallmeyer +3
Pre-trained Language Models (PLMs) are known to contain various kinds of knowledge. One method to infer relational knowledge is through the use of cloze-style prompts, where a mode…
TACO -- Twitter Arguments from COnversations
Marc Feger, Stefan Dietze
Twitter has emerged as a global hub for engaging in online conversations and as a research corpus for various disciplines that have recognized the significance of its user-generate…
GSAP-NER: A Novel Task, Corpus, and Baseline for Scholarly Entity Extraction Focused on Machine Learning Models and Datasets
Wolfgang Otto, Matthäus Zloch, Lu Gan +2
Named Entity Recognition (NER) models play a crucial role in various NLP tasks, including information extraction (IE) and text understanding. In academic writing, references to mac…
SciTweets -- A Dataset and Annotation Framework for Detecting Scientific Online Discourse
Salim Hafid, Sebastian Schellhammer, Sandra Bringay +2
Scientific topics, claims and resources are increasingly debated as part of online discourse, where prominent examples include discourse related to COVID-19 or climate change. This…