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Common Sense Reasoning

27 papers with code · Reasoning

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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Latest papers with code

CITE: A Corpus of Image-Text Discourse Relations

12 Apr 2019malihealikhani/CITE

This paper presents a novel crowd-sourced resource for multimodal discourse: our resource characterizes inferences in image-text contexts in the domain of cooking recipes in the form of coherence relations.

COMMON SENSE REASONING

1
12 Apr 2019

Language Models are Unsupervised Multitask Learners

Preprint 2019 openai/gpt-2

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

 SOTA for Language Modelling on Penn Treebank (Word Level) (using extra training data)

COMMON SENSE REASONING DOCUMENT SUMMARIZATION LANGUAGE MODELLING MACHINE TRANSLATION QUESTION ANSWERING READING COMPREHENSION

5,154
14 Feb 2019

Compositional Language Understanding with Text-based Relational Reasoning

7 Nov 2018koustuvsinha/clutrr

Neural networks for natural language reasoning have largely focused on extractive, fact-based question-answering (QA) and common-sense inference.

COMMON SENSE REASONING LANGUAGE MODELLING QUESTION ANSWERING RELATIONAL REASONING

21
07 Nov 2018

pair2vec: Compositional Word-Pair Embeddings for Cross-Sentence Inference

20 Oct 2018ghlee0304/NLP-with-tensorflow-pytorch

Reasoning about implied relationships (e. g., paraphrastic, common sense, encyclopedic) between pairs of words is crucial for many cross-sentence inference problems.

COMMON SENSE REASONING WORD EMBEDDINGS

0
20 Oct 2018

SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inference

EMNLP 2018 chiahsuan156/Question-Answering_Resources_Papers

Given a partial description like "she opened the hood of the car," humans can reason about the situation and anticipate what might come next ("then, she examined the engine").

COMMON SENSE REASONING NATURAL LANGUAGE INFERENCE

0
16 Aug 2018

Incorporating Chinese Characters of Words for Lexical Sememe Prediction

ACL 2018 thunlp/Character-enhanced-Sememe-Prediction

However, existing methods of lexical sememe prediction typically rely on the external context of words to represent the meaning, which usually fails to deal with low-frequency and out-of-vocabulary words.

COMMON SENSE REASONING

13
17 Jun 2018

A Simple Method for Commonsense Reasoning

7 Jun 2018tensorflow/models

For example, it is difficult to use neural networks to tackle the Winograd Schema dataset~\cite{levesque2011winograd}.

COMMON SENSE REASONING

51,704
07 Jun 2018