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20192025
most citedNLNDE: The Neither-Language-Nor-Domain-Experts' Way of Spanish Medical Document De-Identification

11 citations · 31 across the 10 of their papers we have counts for

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17 papers · 1 filter

cs.CL2025

Language Mixing in Reasoning Language Models: Patterns, Impact, and Internal Causes

Mingyang Wang, Lukas Lange, Heike Adel +3

Reasoning language models (RLMs) excel at complex tasks by leveraging a chain-of-thought process to generate structured intermediate steps. However, language mixing, i.e., reasonin…

cs.CL2025

Lost in Multilinguality: Dissecting Cross-lingual Factual Inconsistency in Transformer Language Models

Mingyang Wang, Heike Adel, Lukas Lange +4

Multilingual language models (MLMs) store factual knowledge across languages but often struggle to provide consistent responses to semantically equivalent prompts in different lang…

cs.CL20252 cited

Bring Your Own Knowledge: A Survey of Methods for LLM Knowledge Expansion

Mingyang Wang, Alisa Stoll, Lukas Lange +3

Adapting large language models (LLMs) to new and diverse knowledge is essential for their lasting effectiveness in real-world applications. This survey provides an overview of stat…

cs.CL2024

Better Call SAUL: Fluent and Consistent Language Model Editing with Generation Regularization

Mingyang Wang, Lukas Lange, Heike Adel +2

To ensure large language models contain up-to-date knowledge, they need to be updated regularly. However, model editing is challenging as it might also affect knowledge that is unr…

cs.CL2021

Boosting Transformers for Job Expression Extraction and Classification in a Low-Resource Setting

Lukas Lange, Heike Adel, Jannik Strötgen

In this paper, we explore possible improvements of transformer models in a low-resource setting. In particular, we present our approaches to tackle the first two of three subtasks…

cs.CL2021

To Share or not to Share: Predicting Sets of Sources for Model Transfer Learning

Lukas Lange, Jannik Strötgen, Heike Adel +1

In low-resource settings, model transfer can help to overcome a lack of labeled data for many tasks and domains. However, predicting useful transfer sources is a challenging proble…