Papers by Kianté Brantley

2 papers
Interactive Text Generation (2023.emnlp-main)

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Challenge: Advances in generative modeling have made it possible to automatically generate high-quality texts, code, and images, but they can be unsatisfactory in many respects.
Approach: They propose a task that allows training generation models interactively without the costs of involving real users.
Outcome: The proposed model trains with Imitation Learning without the cost of involving real users and is superior to non-interactive models.
Active Imitation Learning with Noisy Guidance (2020.acl-main)

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Challenge: Structured prediction methods learn models to map inputs to complex outputs with internal dependencies.
Approach: They propose an algorithm that mimics an expert's choice at any queried state . they apply LEAQI to three sequence labelling tasks to reduce query costs .
Outcome: The proposed algorithm shows better accuracies over a passive approach.

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