An answer-paragraph-selection-based retriever improves non-factoid QA in four Indic languages on three LLMs, with average semantic gains of 4% and token-level ROUGE gains of 47% over a full-context baseline, while using less compute.
InProceedings of the 20th ACM SIGKDD international conference on Knowl- edge discovery and data mining, pages 1156–1165
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Long-context Non-factoid Question Answering in Indic Languages
An answer-paragraph-selection-based retriever improves non-factoid QA in four Indic languages on three LLMs, with average semantic gains of 4% and token-level ROUGE gains of 47% over a full-context baseline, while using less compute.