Jonathan H. Clark — accepted AI-conference papers

2023

Cross-lingual Open-Retrieval Question Answering for African Languages

Odunayo Ogundepo, Tajuddeen Gwadabe, Clara E. Rivera, Jonathan H. Clark, Sebastian Ruder, David Ifeoluwa Adelani +38

EMNLP 2023long findings

African languages have far less in-language content available digitally, making it challenging for question answering systems to satisfy the information needs of users. Cross-lingual open-retrieval question answering (XOR QA) systems -- those that retrieve answer content from other languages while s…

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2023

Evaluating and Modeling Attribution for Cross-Lingual Question Answering

Benjamin Muller, John Frederick Wieting, Jonathan H. Clark, Tom Kwiatkowski, Sebastian Ruder, Livio Baldini Soares +3

EMNLP 2023long main

Trustworthy answer content is abundant in many high-resource languages and is instantly accessible through question answering systems — yet this content can be hard to access for those that do not speak these languages. The leap forward in cross-lingual modeling quality offered by generative languag…

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2023

XTREME-UP: A User-Centric Scarce-Data Benchmark for Under-Represented Languages

Sebastian Ruder, Jonathan H. Clark, Alexander Gutkin, Mihir Kale, Min Ma, Massimo Nicosia +21

EMNLP 2023long findings

Data scarcity is a crucial issue for the development of highly multilingual NLP systems. Yet for many under-represented languages (ULs) --- languages for which NLP research is particularly far behind in meeting user needs --- it is feasible to annotate small amounts of data. Motivated by this, we pr…

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