8 citations · 16 across the 47 of their papers we have counts for
19 papers · 1 filter
Assessing Web Search Credibility and Response Groundedness in Chat Assistants
Ivan Vykopal, Matúš Pikuliak, Simon Ostermann +1
Chat assistants increasingly integrate web search functionality, enabling them to retrieve and cite external sources. While this promises more reliable answers, it also raises the…
Sparse Subnetwork Enhancement for Underrepresented Languages in Large Language Models
Daniil Gurgurov, Tanja Baeumel, Josef van Genabith +1
Large language models (LLMs) exhibit substantial performance disparities across languages, particularly between high- and low-resource settings. We propose a framework for improvin…
Multilingual Datasets for Custom Input Extraction and Explanation Requests Parsing in Conversational XAI Systems
Qianli Wang, Tatiana Anikina, Nils Feldhus +6
Conversational explainable artificial intelligence (ConvXAI) systems based on large language models (LLMs) have garnered considerable attention for their ability to enhance user co…
Modular Arithmetic: Language Models Solve Math Digit by Digit
Tanja Baeumel, Daniil Gurgurov, Yusser al Ghussin +2
While recent work has begun to uncover the internal strategies that Large Language Models (LLMs) employ for simple arithmetic tasks, a unified understanding of their underlying mec…
Cross-Prompt Encoder for Low-Performing Languages
Beso Mikaberidze, Teimuraz Saghinadze, Simon Ostermann +1
Soft prompts have emerged as a powerful alternative to adapters in parameter-efficient fine-tuning (PEFT), enabling large language models (LLMs) to adapt to downstream tasks withou…
The AI Language Proficiency Monitor -- Tracking the Progress of LLMs on Multilingual Benchmarks
David Pomerenke, Jonas Nothnagel, Simon Ostermann
To ensure equitable access to the benefits of large language models (LLMs), it is essential to evaluate their capabilities across the world's languages. We introduce the AI Languag…