Mahammad Ismayilzada

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Defeasibility in causal reasoning implies that the causal relationship between cause and effect can be strengthened or weakened. Namely, the causal strength between cause and effect should increase or decrease with the incorporation of strengthening argume ...

Recent efforts in natural language processing (NLP) commonsense reasoning research have yielded a considerable number of new datasets and benchmarks. However, most of these datasets formulate commonsense reasoning challenges in artificial scenarios that ar ...

Language models (LMs) have recently shown remarkable performance on reasoning tasks by explicitly generating intermediate inferences, e.g., chain-of-thought prompting. However, these intermediate inference steps may be in- appropriate deductions from the i ...

In this paper, we present kogito, an open-source tool for generating commonsense inferences about situations described in text. kogito provides an intuitive and extensible interface to interact with natural language generation models that can be used for h ...

Mahammad Ismayilzada

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Exploring Defeasibility in Causal Reasoning

CRoW: Benchmarking Commonsense Reasoning in Real-World Tasks

REFINER: Reasoning Feedback on Intermediate Representations

kogito: A Commonsense Knowledge Inference Toolkit