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Found 4 papers, 2 papers with code
FairytaleCQA: Integrating a Commonsense Knowledge Graph into Children's Storybook Narratives
AI models (including LLM) often rely on narrative question-answering (QA) datasets to provide customized QA functionalities to support downstream children education applications; however, existing datasets only include QA pairs that are grounded within the given storybook content, but children can learn more when teachers refer the storybook content to real-world knowledge (e. g., commonsense knowledge).
Mental-LLM: Leveraging Large Language Models for Mental Health Prediction via Online Text Data
More importantly, our experiments show that instruction finetuning can significantly boost the performance of LLMs for all tasks simultaneously.
Build a Robust QA System with Transformer-based Mixture of Experts
In this paper, we show that our combination of best architecture and data augmentation techniques achieves a 53. 477 F1 score in the out-of-domain evaluation, which is a 9. 52% performance gain over the baseline.
