# Learning to answer questions

arXiv: https://arxiv.org/abs/1309.1125 · HTML: https://mlsanity.com/paper/1309.1125/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Sep 2013.

## Built on by (most cited first, 2 of 2)

- [A Survey on Benchmarks of Multimodal Large Language Models](https://mlsanity.com/paper/2408.08632/) (2024)
- [MISAR: A Multimodal Instructional System with Augmented Reality](https://mlsanity.com/paper/2310.11699/) (2023)

## Abstract (arXiv)

We present an open-domain Question-Answering system that learns to answer questions based on successful past interactions. We follow a pattern-based approach to Answer-Extraction, where (lexico-syntactic) patterns that relate a question to its answer are automatically learned and used to answer future questions. Results show that our approach contributes to the system's best performance when it is conjugated with typical Answer-Extraction strategies. Moreover, it allows the system to learn with the answered questions and to rectify wrong or unsolved past questions.