Papers › Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks

Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks

19 Feb 2015arXiv:1502.05698archive 2025-07-28

Jason Weston, Antoine Bordes, Sumit Chopra, Alexander M. Rush, Bart van Merriënboer, Armand Joulin, Tomas Mikolov

One long-term goal of machine learning research is to produce methods that are applicable to reasoning and natural language, in particular building an intelligent dialogue agent. To measure progress towards that goal, we argue for the usefulness of a set of proxy tasks that evaluate reading comprehension via question answering. Our tasks measure understanding in several ways: whether a system is able to answer questions via chaining facts, simple induction, deduction and many more. The tasks are designed to be prerequisites for any system that aims to be capable of conversing with a human. We believe many existing learning systems can currently not solve them, and hence our aim is to classify these tasks into skill sets, so that researchers can identify (and then rectify) the failings of their systems. We also extend and improve the recently introduced Memory Networks model, and show it is able to solve some, but not all, of the tasks.

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20 repositories listed; official and paper-mentioned ones first.

facebook/bAbI-tasks officialmentioned in papermentioned on GitHubtorchNOASSERTION report
AlexKuhnle/ShapeWorld mentioned on GitHubtf report
HSabbar/Question-Answering mentioned on GitHubtf report
aykutaaykut/Memory-Networks mentioned on GitHub report
booydar/babilong mentioned on GitHubpytorchApache-2.0 report
cstghitpku/GateMemN2N mentioned on GitHubtfMIT report
domluna/memn2n mentioned on GitHubtf report
facebookarchive/babi-tasks mentioned on GitHubtorchNOASSERTION report
facebookresearch/ParlAI mentioned on GitHubpytorchMIT report
ishalyminov/memn2n mentioned on GitHubtf report
jojonki/MemoryNetworks mentioned on GitHubpytorch report
kirubarajan/roft mentioned on GitHubMIT report
kirubarajan/trick mentioned on GitHubMIT report
nastasiaF/5DEEP mentioned on GitHub report
nbansal90/bAbi_QA mentioned on GitHub report
qapitan/babi-marcus mentioned on GitHubtorchNOASSERTION report
sayakbanerjee1999/Chat-Bot mentioned on GitHub report
uwnlp/qrn mentioned on GitHubtfMIT report

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position_encoding domluna/memn2n/memn2n/memn2n.py community (archive-listed) ran · honoured contract fingerprinted MIT (permissive) · 8abcd06d5ce60851 · report
parse_stories prashil2792/Question-Answering-System-Deep-Learning/memorynetwork.py community (archive-listed) unverified no licence file found · pointer only · 9d142ef2a5e220be · report
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Question AnsweringReading Comprehension

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