Papers by Josh Arnold

2 papers
Building Task-Oriented Visual Dialog Systems Through Alternative Optimization Between Dialog Policy and Language Generation (D19-1)

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Challenge: Current approaches to visual dialog learning involve an end-to-end framework that maps the multi-modal context to a deep vector and in order to decode a natural dialog response.
Approach: They propose a framework that trains a RL policy for image guessing and a seq2seq model to improve dialog quality.
Outcome: The proposed framework achieves state-of-the-art performance on a guessWhich task . it can be applied to a wide range of tasks including assisting blind people .
LEGOEval: An Open-Source Toolkit for Dialogue System Evaluation via Crowdsourcing (2021.acl-demo)

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Challenge: Currently, researchers use automatic metrics and human evaluation to evaluate dialogue systems.
Approach: They propose to use a Python API to easily evaluate dialogue systems using Amazon Mechanical Turk.
Outcome: The open-source toolkit provides a fast, consistent method for reproducing human evaluation results.

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