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Found 40 papers, 20 papers with code
Summarization of German Court Rulings
In this paper, we propose the task of automatic summarization of German court rulings.
Differential Privacy in Natural Language Processing The Story So Far
As the tide of Big Data continues to influence the landscape of Natural Language Processing (NLP), the utilization of modern NLP methods has grounded itself in this data, in order to tackle a variety of text-based tasks.
Clause Topic Classification in German and English Standard Form Contracts
So-called standard form contracts, i. e. contracts that are drafted unilaterally by one party, like terms and conditions of online shops or terms of services of social networks, are cornerstones of our modern economy.
Structured Extraction of Terms and Conditions from German and English Online Shops
While content extraction, in general, is a well-researched field and many open source libraries are available, our evaluation shows, that existing solutions cannot extract Terms and Conditions in sufficient quality, mainly because of their special structure.
TUM sebis at GermEval 2022: A Hybrid Model Leveraging Gaussian Processes and Fine-Tuned XLM-RoBERTa for German Text Complexity Analysis
The task of quantifying the complexity of written language presents an interesting endeavor, particularly in the opportunity that it presents for aiding language learners.
NLP for Consumer Protection: Battling Illegal Clauses in German Terms and Conditions in Online Shopping
Government and non-government organisations (NGOs) for consumer protection battle such terms on behalf of consumers, who often hesitate to take on legal actions themselves.
Towards A Structured Overview of Use Cases for Natural Language Processing in the Legal Domain: A German Perspective
In recent years, the field of Legal Tech has risen in prevalence, as the Natural Language Processing (NLP) and legal disciplines have combined forces to digitalize legal processes.
Improving Health Question Answering with Reliable and Time-Aware Evidence Retrieval
In today's digital world, seeking answers to health questions on the Internet is a common practice.
A Comparative Analysis of Word-Level Metric Differential Privacy: Benchmarking The Privacy-Utility Trade-off
The application of Differential Privacy to Natural Language Processing techniques has emerged in relevance in recent years, with an increasing number of studies published in established NLP outlets.
Enterprise Use Cases Combining Knowledge Graphs and Natural Language Processing
Knowledge management is a critical challenge for enterprises in today's digital world, as the volume and complexity of data being generated and collected continue to grow incessantly.
Comparing Knowledge Sources for Open-Domain Scientific Claim Verification
We test the final verdict prediction of systems on four datasets of biomedical and health claims in different settings.
A Comparative Analysis of Conversational Large Language Models in Knowledge-Based Text Generation
In this study, we conduct an empirical analysis of conversational large language models in generating natural language text from semantic triples.
Evaluating Large Language Models in Semantic Parsing for Conversational Question Answering over Knowledge Graphs
Conversational question answering systems often rely on semantic parsing to enable interactive information retrieval, which involves the generation of structured database queries from a natural language input.
Diversifying Knowledge Enhancement of Biomedical Language Models using Adapter Modules and Knowledge Graphs
In this paper, we develop an approach that uses lightweight adapter modules to inject structured biomedical knowledge into pre-trained language models (PLMs).
From Data to Dialogue: Leveraging the Structure of Knowledge Graphs for Conversational Exploratory Search
Exploratory search is an open-ended information retrieval process that aims at discovering knowledge about a topic or domain rather than searching for a specific answer or piece of information.
HealthFC: Verifying Health Claims with Evidence-Based Medical Fact-Checking
In the digital age, seeking health advice on the Internet has become a common practice.
SoK: Assessing the State of Applied Federated Machine Learning
Machine Learning (ML) has shown significant potential in various applications; however, its adoption in privacy-critical domains has been limited due to concerns about data privacy.
Exploring the Landscape of Natural Language Processing Research
As an efficient approach to understand, generate, and process natural language texts, research in natural language processing (NLP) has exhibited a rapid spread and wide adoption in recent years.
AspectCSE: Sentence Embeddings for Aspect-based Semantic Textual Similarity Using Contrastive Learning and Structured Knowledge
Generic sentence embeddings provide a coarse-grained approximation of semantic textual similarity but ignore specific aspects that make texts similar.
Efficient Domain Adaptation of Sentence Embeddings Using Adapters
Instead, we only train a small number of additional parameters while keeping the weights of the underlying sentence embedding model fixed.
Challenges in Domain-Specific Abstractive Summarization and How to Overcome them
Large Language Models work quite well with general-purpose data and many tasks in Natural Language Processing.
Scientific Fact-Checking: A Survey of Resources and Approaches
In particular, scientific fact-checking is the variation of the task concerned with verifying claims rooted in scientific knowledge.
Unlocking the Potential of Collaborative AI -- On the Socio-technical Challenges of Federated Machine Learning
This research investigates the challenges of prevailing collaborative business models and distinct aspects of Federated Machine Learning.
Sebis at SemEval-2023 Task 7: A Joint System for Natural Language Inference and Evidence Retrieval from Clinical Trial Reports
The first one is a pipeline system that models the two tasks separately, while the second one is a joint system that learns the two tasks simultaneously with a shared representation and a multi-task learning approach.
Voice-Based Conversational Agents and Knowledge Graphs for Improving News Search in Assisted Living
By leveraging graph databases to semantically structure news data and implementing an intuitive voice-based interface, our system can help care-dependent people to easily discover relevant news articles and give personalized recommendations.
Investigating Conversational Search Behavior For Domain Exploration
Conversational search has evolved as a new information retrieval paradigm, marking a shift from traditional search systems towards interactive dialogues with intelligent search agents.
Evaluating Unsupervised Text Classification: Zero-shot and Similarity-based Approaches
Text classification of unseen classes is a challenging Natural Language Processing task and is mainly attempted using two different types of approaches.
Ranked #1 on
Unsupervised Text Classification
on AG News
(F1-score metric)
Semantic Similarity-Based Clustering of Findings From Security Testing Tools
Over the last years, software development in domains with high security demands transitioned from traditional methodologies to uniting modern approaches from software development and operations (DevOps).
Lbl2Vec: An Embedding-Based Approach for Unsupervised Document Retrieval on Predefined Topics
When successively retrieving documents on different predefined topics from publicly available and commonly used datasets, we achieved an average area under the receiver operating characteristic curve value of 0. 95 on one dataset and 0. 92 on another.
Ranked #1 on
Unsupervised Text Classification
on AG News
PatternRank: Leveraging Pretrained Language Models and Part of Speech for Unsupervised Keyphrase Extraction
Keyphrase extraction is the process of automatically selecting a small set of most relevant phrases from a given text.
Ranked #2 on
Keyphrase Extraction
on Inspec
A Decade of Knowledge Graphs in Natural Language Processing: A Survey
In pace with developments in the research field of artificial intelligence, knowledge graphs (KGs) have attracted a surge of interest from both academia and industry.
Differential Privacy in Natural Language Processing: The Story So Far
As such, the question of privacy in NLP has gained fervor in recent years, coinciding with the development of new Privacy-Enhancing Technologies (PETs).
CodeTrans: Towards Cracking the Language of Silicon's Code Through Self-Supervised Deep Learning and High Performance Computing
Simultaneously, the transformer model, especially its combination with transfer learning, has been proven to be a powerful technique for natural language processing tasks.
MucLex: A German Lexicon for Surface Realisation
Language resources for languages other than English are often scarce.
SimpleNLG-DE: Adapting SimpleNLG 4 to German
SimpleNLG is a popular open source surface realiser for the English language.
Multi-Task Deep Learning for Legal Document Translation, Summarization and Multi-Label Classification
A potential solution to this problem is multi-task DL to enable transfer learning.
Stop Illegal Comments: A Multi-Task Deep Learning Approach
Deep learning methods are often difficult to apply in the legal domain due to the large amount of labeled data required by deep learning methods.
Named-Entity Linking Using Deep Learning For Legal Documents: A Transfer Learning Approach
However, this paper focuses especially on the aspect of applying transfer learning approach using networks trained for NEL to legal documents.
SaToS: Assessing and Summarising Terms of Services from German Webshops
Every time we buy something online, we are confronted with Terms of Services.
Evaluating Natural Language Understanding Services for Conversational Question Answering Systems
Conversational interfaces recently gained a lot of attention.
