Papers by Jeremy Weiss

2 papers
ESPRIT: Explaining Solutions to Physical Reasoning Tasks (2020.acl-main)

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Challenge: Neural networks lack the ability to reason about qualitative physics and cannot generalize to scenarios and tasks unseen during training.
Approach: They propose a framework for reasoning about qualitative physics in natural language that generates interpretable descriptions of physical events.
Outcome: The proposed framework generates explanations of how the physical simulation will causally evolve so that an agent or a human can reason about a solution using interpretable descriptions.
AnEMIC: A Framework for Benchmarking ICD Coding Models (2022.emnlp-demos)

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Challenge: Diagnostic coding is the task of assigning diagnosis codes defined by the ICD (International Classification of Diseases) standard to patient visits based on clinical notes.
Approach: They propose to use an ICD coding framework to train and benchmark models . they correct errors in preprocessing and provide an interactive demo to analyze the models based on custom inputs.
Outcome: The framework corrects errors in preprocessing and provides key models and weights trained on correctly preprocessed datasets.

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