Common Sense 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 without code
Reasoning-Driven Question-Answering for Natural Language Understanding
In the second part, we propose two new challenge datasets.
COMMON SENSE REASONING NATURAL LANGUAGE INFERENCE QUESTION ANSWERING READING COMPREHENSION
Learn How to Cook a New Recipe in a New House: Using Map Familiarization, Curriculum Learning, and Common Sense to Learn Families of Text-Based Adventure Games
We consider the task of learning to play families of text-based computer adventure games, i. e., fully textual environments with a common theme (e. g. cooking) and goal (e. g. prepare a meal from a recipe) but with different specifics; new instances of such games are relatively straightforward for humans to master after a brief exposure to the genre but have been curiously difficult for computer agents to learn.
Processamento de linguagem natural em Português e aprendizagem profunda para o domínio de Óleo e Gás
This paper presents a literature review about the main techniques for deep learning NLP and their major applications for O&G domain in Portuguese.
Learning Emphasis Selection for Written Text in Visual Media from Crowd-Sourced Label Distributions
In visual communication, text emphasis is used to increase the comprehension of written text to convey the author{'}s intent.
Fine-tuning Pre-Trained Transformer Language Models to Distantly Supervised Relation Extraction
Distantly supervised relation extraction is widely used to extract relational facts from text, but suffers from noisy labels.
COMMON SENSE REASONING LANGUAGE MODELLING RELATION CLASSIFICATION
The KnowRef Coreference Corpus: Removing Gender and Number Cues for Difficult Pronominal Anaphora Resolution
To explain this performance gap, we show empirically that state-of-the art models often fail to capture context, instead relying on the gender or number of candidate antecedents to make a decision.
COMMON SENSE REASONING COREFERENCE RESOLUTION DATA AUGMENTATION
Does it Make Sense? And Why? A Pilot Study for Sense Making and Explanation
Introducing common sense to natural language understanding systems has received increasing research attention.
Explain Yourself! Leveraging Language Models for Commonsense Reasoning
Deep learning models perform poorly on tasks that require commonsense reasoning, which often necessitates some form of world-knowledge or reasoning over information not immediately present in the input.
A Statistical View on Synthetic Aperture Imaging for Occlusion Removal
Synthetic apertures find applications in many fields, such as radar, radio telescopes, microscopy, sonar, ultrasound, LiDAR, and optical imaging.
Learning Spatial Common Sense With Geometry-Aware Recurrent Networks
We integrate two powerful ideas, geometry and deep visual representation learning, into recurrent network architectures for mobile visual scene understanding.
COMMON SENSE REASONING REPRESENTATION LEARNING SCENE UNDERSTANDING