3 citations · 5 across the 23 of their papers we have counts for
6 papers · 1 filter
Adapting Multilingual LLMs to Low-Resource Languages with Knowledge Graphs via Adapters
Daniil Gurgurov, Mareike Hartmann, Simon Ostermann
This paper explores the integration of graph knowledge from linguistic ontologies into multilingual Large Language Models (LLMs) using adapters to improve performance for low-resou…
Cross-Refine: Improving Natural Language Explanation Generation by Learning in Tandem
Qianli Wang, Tatiana Anikina, Nils Feldhus +3
Natural language explanations (NLEs) are vital for elucidating the reasoning behind large language model (LLM) decisions. Many techniques have been developed to generate NLEs using…
Soft Language Prompts for Language Transfer
Ivan Vykopal, Simon Ostermann, Marián Šimko
Cross-lingual knowledge transfer, especially between high- and low-resource languages, remains challenging in natural language processing (NLP). This study offers insights for impr…
Probing Context Localization of Polysemous Words in Pre-trained Language Model Sub-Layers
Soniya Vijayakumar, Josef van Genabith, Simon Ostermann
In the era of high performing Large Language Models, researchers have widely acknowledged that contextual word representations are one of the key drivers in achieving top performan…
CoXQL: A Dataset for Parsing Explanation Requests in Conversational XAI Systems
Qianli Wang, Tatiana Anikina, Nils Feldhus +2
Conversational explainable artificial intelligence (ConvXAI) systems based on large language models (LLMs) have garnered significant interest from the research community in natural…
Soft Begging: Modular and Efficient Shielding of LLMs against Prompt Injection and Jailbreaking based on Prompt Tuning
Simon Ostermann, Kevin Baum, Christoph Endres +2
Prompt injection (both direct and indirect) and jailbreaking are now recognized as significant issues for large language models (LLMs), particularly due to their potential for harm…