Vitaly Nikolaev — accepted AI-conference papers

2023

SEAHORSE: A Multilingual, Multifaceted Dataset for Summarization Evaluation

Elizabeth Clark, Shruti Rijhwani, Sebastian Gehrmann, Joshua Maynez, Roee Aharoni, Vitaly Nikolaev +4

EMNLP 2023long main

Reliable automatic evaluation of summarization systems is challenging due to the multifaceted and subjective nature of the task. This is especially the case for languages other than English, where human evaluations are scarce. In this work, we introduce SEAHORSE, a dataset for multilingual, multifac…

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2023

TaTA: A Multilingual Table-to-Text Dataset for African Languages

Sebastian Gehrmann, Sebastian Ruder, Vitaly Nikolaev, Jan A. Botha, Michael Chavinda, Ankur P Parikh +1

EMNLP 2023long findings

Existing data-to-text generation datasets are mostly limited to English. To address this lack of data, we create Table-to-Text in African languages (TaTA), the first large multilingual table-to-text dataset with a focus on African languages. We created TaTA by transcribing figures and accompanying t…

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2021

SynthBio: A Case Study in Faster Curation of Text Datasets

Ann Yuan, Daphne Ippolito, Vitaly Nikolaev, Chris Callison-Burch, Andy Coenen, Sebastian Gehrmann

NeurIPS 2021poster

NLP researchers need more, higher-quality text datasets. Human-labeled datasets are expensive to collect, while datasets collected via automatic retrieval from the web such as WikiBio [Lebret 2016] are noisy and can include undesired biases. Moreover, data sourced from the web is often included in d…

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