7 citations · 24 across the 31 of their papers we have counts for
33 papers
The Curious Case of Factual (Mis)Alignment between LLMs' Short- and Long-Form Answers
Saad Obaid ul Islam, Anne Lauscher, Goran Glavaš
Large language models (LLMs) can correctly answer "When was Einstein born?" yet fail to provide the same date when writing about Einstein's life revealing a fundamental inconsisten…
ReCoVeR the Target Language: Language Steering without Sacrificing Task Performance
Hannah Sterz, Fabian David Schmidt, Goran Glavaš +1
As they become increasingly multilingual, Large Language Models (LLMs) exhibit more language confusion, i.e., they tend to generate answers in a language different from the languag…
On Generalization across Measurement Systems: LLMs Entail More Test-Time Compute for Underrepresented Cultures
Minh Duc Bui, Kyung Eun Park, Goran Glavaš +2
Measurement systems (e.g., currencies) differ across cultures, but the conversions between them are well defined so that humans can state facts using any measurement system of thei…
On the Potential of Large Language Models to Solve Semantics-Aware Process Mining Tasks
Adrian Rebmann, Fabian David Schmidt, Goran Glavaš +1
Large language models (LLMs) have shown to be valuable tools for tackling process mining tasks. Existing studies report on their capability to support various data-driven process a…
On Synthesizing Data for Context Attribution in Question Answering
Gorjan Radevski, Kiril Gashteovski, Shahbaz Syed +11
Question Answering (QA) accounts for a significant portion of LLM usage "in the wild". However, LLMs sometimes produce false or misleading responses, also known as "hallucinations"…
MVL-SIB: A Massively Multilingual Vision-Language Benchmark for Cross-Modal Topical Matching
Fabian David Schmidt, Florian Schneider, Chris Biemann +1
Existing multilingual vision-language (VL) benchmarks often only cover a handful of languages. Consequently, evaluations of large vision-language models (LVLMs) predominantly targe…