IBM Research AI @ IJCAI 2019

At IJCAI-19, IBM Research AI will present technical papers exploring a variety of topics in AI including neurosymbolic reasoning, explainability, adversarial robustness, computational linguistics, graph analysis, optimization, and reinforcement learning.

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Bank Guarantees Go Digital with Blockchain

IBM has developed Lygon, a first-of-a-kind platform to digitise and transform the bank guarantee process.

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Introducing AI Explainability 360

IBM Research AI announced AI Explainability 360, a comprehensive open-source toolkit of state-of-the-art algorithms that support the interpretability and explainability of machine learning models.

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Answering Complex Questions using Neural Program Induction

At ACL 2019, IBM researchers released a paper detailing the model they trained to answer complex questions using Neural Program Induction, which allows an AI model can be taught to procedurally decompose a complex task into a program.

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Adversarial Learning and Zeroth Order Optimization for Machine Learning and Data Mining

There is a growing number of adversarial attacks and nefarious behaviors aimed at AI systems. To combat this, IBM Research AI will present multiple papers that yield new scientific discoveries and recommendations related to adversarial learning at KDD 2019.

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IBM Research AI at KDD 2019

At KDD 2019, IBM Research AI will present technical papers describing the latest results in deep learning for graphs, adversarial learning, text understanding, and data science for healthcare, financial crimes, and scientific discovery.

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Help build the next generation of AI-driven dialog systems

IBM Research AI and the University of Michigan are organizing a public competition to inspire and evaluate novel approaches that will lead to the next generation of AI-driven dialog systems.

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Overcoming Challenges in Building Enterprise AI Assistants

A team of researchers from IBM Research AI and AI Horizons Network-partner the University of Michigan published the papers “A Large-Scale Corpus for Conversation Disentanglement” and “Learning End-to-End Goal-Oriented Dialog with Maximal User Task Success and Minimal Human Agent Use” at ACL 2019. This work address two main challenges in building enterprise AI assistants.

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With HEIDL, Humans and Machines Can Work Together to Cut Through Legalese

At ACL 2019, IBM researchers will present a demonstration of HEIDL, a model that makes it easier and much faster for people to review the effectiveness of natural language labels generated by a deep learning model trained on human-labeled data.

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A New State-of-the-Art Method for Relation Extraction

IBM Research AI and IBM Watson worked together to develop a promising approach that achievies state-of-the-art performance on relation extraction. This work is being presented at ACL 2019.

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Making Sense of Science with Discovery Augmented Summarization

The IBM Science Summarizer, or DimSum, as it was nicknamed by the team for its DIscovery augMented SUMmarization, is a service that tracks scientific papers being published in the area of AI.  The service produces summaries of the papers focused around an information need expressed through natural language queries.

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Four Papers Advance Computational Argumentation in IBM’s Project Debater

The latest work on computational argumentation from the IBM Project Debater research team group is being presented at the ACL 2019 conference. Three papers will be presented at the main conference and one more paper will be presented in the co-located Argument Mining Workshop.

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