1 citations · 1 across the 7 of their papers we have counts for
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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…