168 citations · 471 across the 17 of their papers we have counts for
6 papers · 2 filters
FIAT: Fusing learning paradigms with Instruction-Accelerated Tuning
Xinyi Wang, John Wieting, Jonathan H. Clark
Learning paradigms for large language models (LLMs) currently tend to fall within either in-context learning (ICL) or full fine-tuning. Each of these comes with their own trade-off…
The Devil is in the Errors: Leveraging Large Language Models for Fine-grained Machine Translation Evaluation
Patrick Fernandes, Daniel Deutsch, Mara Finkelstein +7
Automatic evaluation of machine translation (MT) is a critical tool driving the rapid iterative development of MT systems. While considerable progress has been made on estimating a…
XTREME-UP: A User-Centric Scarce-Data Benchmark for Under-Represented Languages
Sebastian Ruder, Jonathan H. Clark, Alexander Gutkin +24
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 re-search is part…
AfriQA: Cross-lingual Open-Retrieval Question Answering for African Languages
Odunayo Ogundepo, Tajuddeen R. Gwadabe, Clara E. Rivera +49
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-lingu…
Evaluating and Modeling Attribution for Cross-Lingual Question Answering
Benjamin Muller, John Wieting, Jonathan H. Clark +6
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 th…
PaLM 2 Technical Report
Rohan Anil, Andrew M. Dai, Orhan Firat +125
We introduce PaLM 2, a new state-of-the-art language model that has better multilingual and reasoning capabilities and is more compute-efficient than its predecessor PaLM. PaLM 2 i…