25 citations · 56 across the 12 of their papers we have counts for
13 papers
Beyond Text: Optimizing RAG with Multimodal Inputs for Industrial Applications
Monica Riedler, Stefan Langer
Large Language Models (LLMs) have demonstrated impressive capabilities in answering questions, but they lack domain-specific knowledge and are prone to hallucinations. Retrieval Au…
CEAR: Automatic construction of a knowledge graph of chemical entities and roles from scientific literature
Stefan Langer, Fabian Neuhaus, Andreas Nürnberger
Ontologies are formal representations of knowledge in specific domains that provide a structured framework for organizing and understanding complex information. Creating ontologies…
FhGenie: A Custom, Confidentiality-preserving Chat AI for Corporate and Scientific Use
Ingo Weber, Hendrik Linka, Daniel Mertens +3
Since OpenAI's release of ChatGPT, generative AI has received significant attention across various domains. These AI-based chat systems have the potential to enhance the productivi…
Domain Adaptive Pretraining for Multilingual Acronym Extraction
Usama Yaseen, Stefan Langer
This paper presents our findings from participating in the multilingual acronym extraction shared task SDU@AAAI-22. The task consists of acronym extraction from documents in 6 lang…
NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation
Kaustubh D. Dhole, Varun Gangal, Sebastian Gehrmann +122
Data augmentation is an important component in the robustness evaluation of models in natural language processing (NLP) and in enhancing the diversity of the data they are trained…
Data Augmentation for Low-Resource Named Entity Recognition Using Backtranslation
Usama Yaseen, Stefan Langer
The state of art natural language processing systems relies on sizable training datasets to achieve high performance. Lack of such datasets in the specialized low resource domains…
Neural Text Classification and Stacked Heterogeneous Embeddings for Named Entity Recognition in SMM4H 2021
Usama Yaseen, Stefan Langer
This paper presents our findings from participating in the SMM4H Shared Task 2021. We addressed Named Entity Recognition (NER) and Text Classification. To address NER we explored B…
Combining Gesture and Voice Control for Mid-Air Manipulation of CAD Models in VR Environments
Markus Friedrich, Stefan Langer, Fabian Frey
Modeling 3D objects in domains like Computer Aided Design (CAD) is time-consuming and comes with a steep learning curve needed to master the design process as well as tool complexi…
Content-based Recommendations for Radio Stations with Deep Learned Audio Fingerprints
Stefan Langer, Liza Obermeier, André Ebert +3
The world of linear radio broadcasting is characterized by a wide variety of stations and played content. That is why finding stations playing the preferred content is a tough task…
Difficulty Classification of Mountainbike Downhill Trails utilizing Deep Neural Networks
Stefan Langer, Robert Müller, Kyrill Schmid +1
The difficulty of mountainbike downhill trails is a subjective perception. However, sports-associations and mountainbike park operators attempt to group trails into different level…
Soccer Team Vectors
Robert Müller, Stefan Langer, Fabian Ritz +3
In this work we present STEVE - Soccer TEam VEctors, a principled approach for learning real valued vectors for soccer teams where similar teams are close to each other in the resu…
Deep Neural Baselines for Computational Paralinguistics
Daniel Elsner, Stefan Langer, Fabian Ritz +2
Detecting sleepiness from spoken language is an ambitious task, which is addressed by the Interspeech 2019 Computational Paralinguistics Challenge (ComParE). We propose an end-to-e…
Apache Lucene as Content-Based-Filtering Recommender System: 3 Lessons Learned
Stefan Langer, Joeran Beel
For the past few years, we used Apache Lucene as recommendation frame-work in our scholarly-literature recommender system of the reference-management software Docear. In this paper…