12 citations · 33 across the 25 of their papers we have counts for
9 papers · 1 filter
Prompting Is All You Need: Multi-view Prompting Large Language Models for Aspect-Based Sentiment Analysis
Nils Constantin Hellwig, Niklas Donhauser, Jakob Fehle +2
Recent work explored the capabilities of Large Language Models (LLMs) in Aspect-Based Sentiment Analysis (ABSA) through few-shot prompting, requiring substantially fewer annotated…
Annotation Quality in Aspect-Based Sentiment Analysis: A Case Study Comparing Experts, Students, Crowdworkers, and Large Language Model
Niklas Donhauser, Jakob Fehle, Nils Constantin Hellwig +3
Aspect-Based Sentiment Analysis (ABSA) enables fine-grained opinion analysis by identifying sentiments toward specific aspects or targets within a text. While ABSA has been widely…
Zero-Shot to Full-Resource: Cross-lingual Transfer Strategies for Aspect-Based Sentiment Analysis
Jakob Fehle, Nils Constantin Hellwig, Udo Kruschwitz +1
Aspect-based Sentiment Analysis (ABSA) extracts fine-grained opinions toward specific aspects within text but remains largely English-focused despite major advances in transformer-…
From Questions to Trust Reports: A LLM-IR Framework for the TREC 2025 DRAGUN Track
Ignacy Alwasiak, Kene Nnolim, Jaclyn Thi +5
The DRAGUN Track at TREC 2025 targets the growing need for effective support tools that help users evaluate the trustworthiness of online news. We describe the UR_Trecking system s…
nchellwig at SemEval-2026 Task 3: Self-Consistent Structured Generation (SCSG) for Dimensional Aspect-Based Sentiment Analysis using Large Language Models
Nils Constantin Hellwig, Jakob Fehle, Udo Kruschwitz +1
We present Self-Consistent Structured Generation (SCSG) for Dimensional Aspect-Based Sentiment Analysis in SemEval-2026 Task 3 (Track A). SCSG enhances prediction reliability by ex…
LLM-as-an-Annotator: Training Lightweight Models with LLM-Annotated Examples for Aspect Sentiment Tuple Prediction
Nils Constantin Hellwig, Jakob Fehle, Udo Kruschwitz +1
Training models for Aspect-Based Sentiment Analysis (ABSA) tasks requires manually annotated data, which is expensive and time-consuming to obtain. This paper introduces LA-ABSA, a…
AnnoABSA: A Web-Based Annotation Tool for Aspect-Based Sentiment Analysis with Retrieval-Augmented Suggestions
Nils Constantin Hellwig, Jakob Fehle, Udo Kruschwitz +1
We introduce AnnoABSA, the first web-based annotation tool to support the full spectrum of Aspect-Based Sentiment Analysis (ABSA) tasks. The tool is highly customizable, enabling f…
Seek and You Shall Find: Design & Evaluation of a Context-Aware Interactive Search Companion
Markus Bink, Marten Risius, Udo Kruschwitz +1
Many users struggle with effective online search and critical evaluation, especially in high-stakes domains like health, while often overestimating their digital literacy. Thus, in…
"Can You Tell Me?": Designing Copilots to Support Human Judgement in Online Information Seeking
Markus Bink, Marten Risius, Udo Kruschwitz +1
Generative AI (GenAI) tools are transforming information seeking, but their fluent, authoritative responses risk overreliance and discourage independent verification and reasoning.…