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Common sense reasoning tasks are intended to require the model to go beyond pattern recognition. Instead, the model should use "common sense" or world knowledge to make inferences.

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Datasets

Greatest papers with code

A Simple Method for Commonsense Reasoning

7 Jun 2018tensorflow/models

Commonsense reasoning is a long-standing challenge for deep learning.

COMMON SENSE REASONING

Language Models are Unsupervised Multitask Learners

Preprint 2019 huggingface/transformers

Natural language processing tasks, such as question answering, machine translation, reading comprehension, and summarization, are typically approached with supervised learning on taskspecific datasets.

 Ranked #1 on Language Modelling on enwik8 (using extra training data)

COMMON SENSE REASONING DATA-TO-TEXT GENERATION DOCUMENT SUMMARIZATION LANGUAGE MODELLING MACHINE TRANSLATION MULTI-TASK LEARNING QUESTION ANSWERING READING COMPREHENSION

DKN: Deep Knowledge-Aware Network for News Recommendation

25 Jan 2018microsoft/recommenders

To solve the above problems, in this paper, we propose a deep knowledge-aware network (DKN) that incorporates knowledge graph representation into news recommendation.

CLICK-THROUGH RATE PREDICTION COMMON SENSE REASONING RECOMMENDATION SYSTEMS

A Neural Conversational Model

19 Jun 2015farizrahman4u/seq2seq

We find that this straightforward model can generate simple conversations given a large conversational training dataset.

COMMON SENSE REASONING NATURAL LANGUAGE UNDERSTANDING

A Hybrid Neural Network Model for Commonsense Reasoning

WS 2019 namisan/mt-dnn

An HNN consists of two component models, a masked language model and a semantic similarity model, which share a BERT-based contextual encoder but use different model-specific input and output layers.

COMMON SENSE REASONING LANGUAGE MODELLING SEMANTIC SIMILARITY SEMANTIC TEXTUAL SIMILARITY

Fake News Detection on Social Media using Geometric Deep Learning

10 Feb 2019gordicaleksa/pytorch-GAT

One of the main reasons is that often the interpretation of the news requires the knowledge of political or social context or 'common sense', which current NLP algorithms are still missing.

COMMON SENSE REASONING FAKE NEWS DETECTION GRAPH CLASSIFICATION