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Found 3 papers, 2 papers with code
Understanding the Effects of Noise in Text-to-SQL: An Examination of the BIRD-Bench Benchmark
This study provides an in-depth analysis of the distribution and types of noise in the widely used BIRD-Bench benchmark and the impact of noise on models.
How Reliable Are Automatic Evaluation Methods for Instruction-Tuned LLMs?
Work on instruction-tuned Large Language Models (LLMs) has used automatic methods based on text overlap and LLM judgments as cost-effective alternatives to human evaluation.
The Impact of Language Adapters in Cross-Lingual Transfer for NLU
Modular deep learning has been proposed for the efficient adaption of pre-trained models to new tasks, domains and languages.
Natural Language Understanding
Zero-Shot Cross-Lingual Transfer
