6 papers
Finetuning LLMs for EvaCun 2025 token prediction shared task
Josef Jon, Ondřej Bojar
In this paper, we present our submission for the token prediction task of EvaCun 2025. Our sys-tems are based on LLMs (Command-R, Mistral, and Aya Expanse) fine-tuned on the task d…
End-to-end Automatic Speech Recognition and Speech Translation: Integration of Speech Foundational Models and LLMs
Nam Luu, Ondřej Bojar
Speech Translation (ST) is a machine translation task that involves converting speech signals from one language to the corresponding text in another language; this task has two dif…
Preliminary Ranking of WMT25 General Machine Translation Systems
Tom Kocmi, Eleftherios Avramidis, Rachel Bawden +25
We present the preliminary rankings of machine translation (MT) systems submitted to the WMT25 General Machine Translation Shared Task, as determined by automatic evaluation metric…
LLM Compression: How Far Can We Go in Balancing Size and Performance?
Sahil Sk, Debasish Dhal, Sonal Khosla +6
Quantization is an essential and popular technique for improving the accessibility of large language models (LLMs) by reducing memory usage and computational costs while maintainin…
MockConf: A Student Interpretation Dataset: Analysis, Word- and Span-level Alignment and Baselines
Dávid Javorský, Ondřej Bojar, François Yvon
In simultaneous interpreting, an interpreter renders a source speech into another language with a very short lag, much sooner than sentences are finished. In order to understand an…
How "Real" is Your Real-Time Simultaneous Speech-to-Text Translation System?
Sara Papi, Peter Polak, Ondřej Bojar +1
Simultaneous speech-to-text translation (SimulST) translates source-language speech into target-language text concurrently with the speaker's speech, ensuring low latency for bette…