t5-1c71e24a·2 events·first seen Aliases: T5
Researchers introduce the Maskability Index (MI), a quantitative metric that estimates whether a knowledge relation is better suited to masked-style or prefix-style prompting in few-shot generation. MI is derived from differences in DepthRank scores between masked and unmasked templates and is evaluated on the ATOMIC2020 knowledge base completion benchmark. Results show MI correlates positively with downstream generation performance, suggesting it can guide template selection for relational knowledge extraction, particularly in low-resource settings.
DeepMind has announced T5Gemma, a new collection of encoder-decoder large language models under the Gemma family. The release extends the Gemma model line beyond its existing decoder-only architecture to include encoder-decoder variants, following the T5 paradigm. Further technical details are sparse in the announcement but the models represent a notable architectural expansion of the open Gemma ecosystem.