A low-rank Gaussian mixture model shows that training task diversity measured by non-overlapping subspace columns improves ICL generalization and shortens learning plateaus for linear attention, with empirical extension to nonlinear cases.
Prompting palm for translation: Assessing strategies and performance
4 Pith papers cite this work, alongside 15 external citations. Polarity classification is still indexing.
4
Pith papers citing it
15
external citations · external index
representative citing papers
SLoW selects low-frequency word dictionaries to boost LLM translation quality and efficiency across 100 languages from FLORES.
DIP interleaves English word translations into non-English prompts to boost multilingual reasoning on synthetic benchmarks spanning 10-200 languages.
PaLM 2 reports state-of-the-art results on language, reasoning, and multilingual tasks with improved efficiency over PaLM.
citing papers explorer
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The Effect of Training Task Diversity on In-Context Learning through the Lens of Low-Dimensional Subspaces
A low-rank Gaussian mixture model shows that training task diversity measured by non-overlapping subspace columns improves ICL generalization and shortens learning plateaus for linear attention, with empirical extension to nonlinear cases.
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SLoW: Select Low-frequency Words! Automatic Dictionary Selection for Translation on Large Language Models
SLoW selects low-frequency word dictionaries to boost LLM translation quality and efficiency across 100 languages from FLORES.
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Dictionary Insertion Prompting for Multilingual Reasoning on Multilingual Large Language Models
DIP interleaves English word translations into non-English prompts to boost multilingual reasoning on synthetic benchmarks spanning 10-200 languages.
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PaLM 2 Technical Report
PaLM 2 reports state-of-the-art results on language, reasoning, and multilingual tasks with improved efficiency over PaLM.