# Comprehension Based Question Answering using Bloom's Taxonomy

Source: [Comprehension Based Question Answering using Bloom's Taxonomy](<https://www.sota2.com/research/paper/68fa6a1d1e209131cea26001>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T23:16:37.291Z

Authors: Pritish Sahu, Michael Cogswell, Sara Rutherford-Quach, Ajay Divakaran

Published: 2021-06-08T19:32:21.000Z

## Abstract

Current pre-trained language models have lots of knowledge, but a more limited ability to use that knowledge. Bloom's Taxonomy helps educators teach children how to use knowledge by categorizing comprehension skills, so we use it to analyze and improve the comprehension skills of large pre-trained language models. Our experiments focus on zero-shot question answering, using the taxonomy to provide proximal context that helps the model answer questions by being relevant to those questions. We show targeting context in this manner improves performance across 4 popular common sense question answer datasets.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2106.04653>)

[PDF](<https://arxiv.org/pdf/2106.04653.pdf>)