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Found 3 papers, 2 papers with code
Look at the Text: Instruction-Tuned Language Models are More Robust Multiple Choice Selectors than You Think
We show that the text answers are more robust to question perturbations than the first token probabilities, when the first token answers mismatch the text answers.
"My Answer is C": First-Token Probabilities Do Not Match Text Answers in Instruction-Tuned Language Models
The open-ended nature of language generation makes the evaluation of autoregressive large language models (LLMs) challenging.
mPLM-Sim: Better Cross-Lingual Similarity and Transfer in Multilingual Pretrained Language Models
Recent multilingual pretrained language models (mPLMs) have been shown to encode strong language-specific signals, which are not explicitly provided during pretraining.
Open-Ended Question Answering
Zero-Shot Cross-Lingual Transfer
