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Found 20 papers, 9 papers with code
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.
On the Influence of Context Size and Model Choice in Retrieval-Augmented Generation Systems
Finally, we show that different general-purpose LLMs excel in the biomedical domain than the encyclopedic one, and that open-domain evidence retrieval in large corpora is challenging.
Step-by-Step Fact Verification System for Medical Claims with Explainable Reasoning
Fact verification (FV) aims to assess the veracity of a claim based on relevant evidence.
Adapter-based Approaches to Knowledge-enhanced Language Models -- A Survey
Knowledge-enhanced language models (KELMs) have emerged as promising tools to bridge the gap between large-scale language models and domain-specific knowledge.
Towards Optimizing a Retrieval Augmented Generation using Large Language Model on Academic Data
Given the growing trend of many organizations integrating Retrieval Augmented Generation (RAG) into their operations, we assess RAG on domain-specific data and test state-of-the-art models across various optimization techniques.
Enhancing Answer Attribution for Faithful Text Generation with Large Language Models
The increasing popularity of Large Language Models (LLMs) in recent years has changed the way users interact with and pose questions to AI-based conversational systems.
DP-MLM: Differentially Private Text Rewriting Using Masked Language Models
The task of text privatization using Differential Privacy has recently taken the form of $\textit{text rewriting}$, in which an input text is obfuscated via the use of generative (large) language models.
MedREQAL: Examining Medical Knowledge Recall of Large Language Models via Question Answering
In recent years, Large Language Models (LLMs) have demonstrated an impressive ability to encode knowledge during pre-training on large text corpora.
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.
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.
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).
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.
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.
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.
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.
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.
TakeLab at SemEval-2019 Task 4: Hyperpartisan News Detection
In this paper, we demonstrate the system built to solve the SemEval-2019 task 4: Hyperpartisan News Detection (Kiesel et al., 2019), the task of automatically determining whether an article is heavily biased towards one side of the political spectrum.
