Code-on-Graph lets LLMs turn retrieved KG facts into Python class instances and generate executable code for reasoning, outperforming prior LLM-KG methods by up to 10.5% on WebQSP, CWQ, and GrailQA.
LLM s Are Few-Shot In-Context Low-Resource Language Learners
3 Pith papers cite this work. Polarity classification is still indexing.
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Broad empirical evaluation finds that fine-tuning heuristics for source-language choice in cross-lingual transfer do not hold reliably under in-context learning.
LLaMA 3.1 extracts visual rating scores from Dutch neuroradiology reports with 87-96% balanced accuracy but only 66-80% on numerical counts, with few-shot prompting raising the latter to 81-92%.
citing papers explorer
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When English Isn't the Best Teacher: Source Language Effects in Cross-Lingual In-Context Learning
Broad empirical evaluation finds that fine-tuning heuristics for source-language choice in cross-lingual transfer do not hold reliably under in-context learning.