Papers with foundation model research

1 papers
Investigating the Multilingual Calibration Effects of Language Model Instruction Tuning (2026.eacl-short)

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Challenge: despite advances in foundation model research, the relationship between large language models and their calibration remains an open area of research.
Approach: They examine a gap in the calibration of large language models within multilingual settings to better understand how data scarcity can potentially lead to different calibration effects.
Outcome: The proposed calibration gap is found in two multilingual benchmarks over 29 and 42 languages.

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