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2020 SEMEVAL SemEval 2020

ETHAN at SemEval-2020 Task 5: Modelling Causal Reasoning in Language Using Neuro-symbolic Cloud Computing

Abstract

AbstractI present ETHAN: Experimental Testing of Hybrid AI Node implemented entirely on free cloud computing infrastructure. The ultimate goal of this research is to create modular reusable hybrid neuro-symbolic architecture for Artificial Intelligence. As a test case I model natural language comprehension of causal relations from open domain text corpus that combines semi-supervised language model (Huggingface Transformers) with constituency and dependency parsers (Allen Institute for Artificial Intelligence.)

🐣 Hot Topic Early Bird β€” causal reasoning
🐝 Cross-Pollinator β€” Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio

Authors

Len Yabloko

Topics

Artificial Intelligence > Core AI > Causal Inference Artificial Intelligence > Core AI > Interpretability

Keywords

causal reasoning language model neuro-symbolic computing dependency parser
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