Search Results for author: Jason Naradowsky

Found 18 papers, 6 papers with code

Rethinking Offensive Text Detection as a Multi-Hop Reasoning Problem

1 code implementation Findings (ACL) 2022 Qiang Zhang, Jason Naradowsky, Yusuke Miyao

We introduce the task of implicit offensive text detection in dialogues, where a statement may have either an offensive or non-offensive interpretation, depending on the listener and context.

Pow-Wow: A Dataset and Study on Collaborative Communication in Pommerman

no code implementations ICML Workshop LaReL 2020 Takuma Yoneda, Matthew R. Walter, Jason Naradowsky

In this work we perform a controlled study of human language use in a competitive team-based game, and search for useful lessons for structuring communication protocol between autonomous agents.

Emergent Communication with World Models

no code implementations22 Feb 2020 Alexander I. Cowen-Rivers, Jason Naradowsky

This provides a visual grounding of the message, similar to an enhanced observation of the world, which may include objects outside of the listening agent's field-of-view.

Visual Grounding

Meta-learning Extractors for Music Source Separation

1 code implementation17 Feb 2020 David Samuel, Aditya Ganeshan, Jason Naradowsky

We propose a hierarchical meta-learning-inspired model for music source separation (Meta-TasNet) in which a generator model is used to predict the weights of individual extractor models.

Meta-Learning Music Source Separation

Represent, Aggregate, and Constrain: A Novel Architecture for Machine Reading from Noisy Sources

no code implementations30 Oct 2016 Jason Naradowsky, Sebastian Riedel

In order to extract event information from text, a machine reading model must learn to accurately read and interpret the ways in which that information is expressed.

Reading Comprehension

Programming with a Differentiable Forth Interpreter

1 code implementation ICML 2017 Matko Bošnjak, Tim Rocktäschel, Jason Naradowsky, Sebastian Riedel

Given that in practice training data is scarce for all but a small set of problems, a core question is how to incorporate prior knowledge into a model.

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