  This technical report describes the development of WangchanLion, an
instruction fine-tuned model focusing on Machine Reading Comprehension (MRC) in
the Thai language. Our model is based on SEA-LION and a collection of
instruction following datasets. To promote open research and reproducibility,
we publicly release all training data, code, and the final model weights under
the Apache-2 license. To assess the contextual understanding capability, we
conducted extensive experimental studies using two Thai MRC datasets, XQuAD and
Iapp_wiki_qa_squad. Experimental results demonstrate the model's ability to
comprehend the context and produce an answer faithful to the reference one in
0-shot and 1-shot settings. In addition, our evaluation goes beyond the
traditional MRC. We propose a new evaluation scheme assessing the answer's
correctness, helpfulness, conciseness, and contextuality. Our code is available
publicly at https://github.com/vistec-AI/WangchanLion.
