1 citations · 1 across the 7 of their papers we have counts for
8 papers
Bias Mitigation in Audio-Enabled LLMs through Adversarial Training and Distillation Methods
Adnan Al Ali, Jindřich Libovický, Anne Lauscher
Audio-enabled large language models (AuLLMs) allow users to interact with them simply by talking to them, without the need for an intermediate transcription. This expands the model…
Predicting Multilingual Classification and Translation Performance of LLMs with Cross-Lingual Alignment -- Is English Enough?
Adnan Al Ali, Kathy Hämmerl, Jindřich Libovický +1
Multilingual large language models (LLMs) have been shown to perform better on non-English classification tasks when the representations of the given language are more aligned to E…
CHALIS: A Challenge Dataset for Language Identification in Difficult Scenarios
Michal Tichý, Jindřich Libovický
We present CHALIS (Challenging Language Identification Samples), a new benchmark dataset explicitly designed to address difficult cases in language identification: cousin languages…
LLM as a Meta-Judge: Synthetic Data for NLP Evaluation Metric Validation
Lukáš Eigler, Jindřich Libovický, David Hurych
Validating evaluation metrics for NLG typically relies on expensive and time-consuming human annotations, which predominantly exist only for English datasets. We propose LLM as a M…
CUS-QA: Local-Knowledge-Oriented Open-Ended Question Answering Dataset
Jindřich Libovický, Jindřich Helcl, Andrei Manea +1
We introduce CUS-QA, a benchmark for evaluation of open-ended regional question answering that encompasses both textual and visual modalities. We also provide strong baselines usin…
Teaching LLMs at Charles University: Assignments and Activities
Jindřich Helcl, Zdeněk Kasner, Ondřej Dušek +4
This paper presents teaching materials, particularly assignments and ideas for classroom activities, from a new course on large language models (LLMs) taught at Charles University.…
Charles Translator: A Machine Translation System between Ukrainian and Czech
Martin Popel, Lucie Poláková, Michal Novák +7
We present Charles Translator, a machine translation system between Ukrainian and Czech, developed as part of a society-wide effort to mitigate the impact of the Russian-Ukrainian…
Enhancing Conceptual Understanding in Multimodal Contrastive Learning through Hard Negative Samples
Philipp J. Rösch, Norbert Oswald, Michaela Geierhos +1
Current multimodal models leveraging contrastive learning often face limitations in developing fine-grained conceptual understanding. This is due to random negative samples during…