1 citations · 1 across the 7 of their papers we have counts for
4 papers · 1 filter
Anthropomimetic Uncertainty: What Verbalized Uncertainty in Language Models is Missing
Dennis Ulmer, Alexandra Lorson, Ivan Titov +1
Human users increasingly communicate with large language models (LLMs), but LLMs suffer from frequent overconfidence in their output, even when its accuracy is questionable, which…
What Are They Filtering Out? An Experimental Benchmark of Filtering Strategies for Harm Reduction in Pretraining Datasets
Marco Antonio Stranisci, Christian Hardmeier
Data filtering strategies are a crucial component to develop safe Large Language Models (LLM), since they support the removal of harmful contents from pretraining datasets. There i…
A comparison of data filtering techniques for English-Polish LLM-based machine translation in the biomedical domain
Jorge del Pozo Lérida, Kamil Kojs, János Máté +2
Large Language Models (LLMs) have become state-of-the-art in Machine Translation (MT), often trained on massive bilingual parallel corpora scraped from the web, that contain low-qu…
With Good MT There is No Need For End-to-End: A Case for Translate-then-Summarize Cross-lingual Summarization
Daniel Varab, Christian Hardmeier
Recent work has suggested that end-to-end system designs for cross-lingual summarization are competitive solutions that perform on par or even better than traditional pipelined des…