6 papers
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…
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…
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…
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…
Learn it or Leave it: Module Composition and Pruning for Continual Learning
Mingyang Wang, Heike Adel, Lukas Lange +2
In real-world environments, continual learning is essential for machine learning models, as they need to acquire new knowledge incrementally without forgetting what they have alrea…
Discourse-Aware In-Context Learning for Temporal Expression Normalization
Akash Kumar Gautam, Lukas Lange, Jannik Strötgen
Temporal expression (TE) normalization is a well-studied problem. However, the predominately used rule-based systems are highly restricted to specific settings, and upcoming machin…