7 papers
Resource-Lean Lexicon Induction for German Dialects
Robert Litschko, Barbara Plank, Diego Frassinelli
Automatic induction of high-quality dictionaries is essential for building lexical resources, yet low-resource languages and dialects pose several challenges: limited access to ann…
Decoupling the Effect of Chain-of-Thought Reasoning: A Human Label Variation Perspective
Beiduo Chen, Tiancheng Hu, Caiqi Zhang +3
Reasoning-tuned LLMs utilizing long Chain-of-Thought (CoT) excel at single-answer tasks, yet their ability to model Human Label Variation--which requires capturing probabilistic am…
Information Asymmetry across Language Varieties: A Case Study on Cantonese-Mandarin and Bavarian-German QA
Renhao Pei, Siyao Peng, Verena Blaschke +2
Large Language Models (LLMs) are becoming a common way for humans to seek knowledge, yet their coverage and reliability vary widely. Especially for local language varieties, there…
Reason to Rote: Rethinking Memorization in Reasoning
Yupei Du, Philipp Mondorf, Silvia Casola +3
Large language models readily memorize arbitrary training instances, such as label noise, yet they perform strikingly well on reasoning tasks. In this work, we investigate how lang…
Make Every Letter Count: Building Dialect Variation Dictionaries from Monolingual Corpora
Robert Litschko, Verena Blaschke, Diana Burkhardt +2
Dialects exhibit a substantial degree of variation due to the lack of a standard orthography. At the same time, the ability of Large Language Models (LLMs) to process dialects rema…
Evaluating Large Language Models for Cross-Lingual Retrieval
Longfei Zuo, Pingjun Hong, Oliver Kraus +2
Multi-stage information retrieval (IR) has become a widely-adopted paradigm in search. While Large Language Models (LLMs) have been extensively evaluated as second-stage reranking…