Papers by Da Tang

2 papers
Subgoal Discovery for Hierarchical Dialogue Policy Learning (D18-1)

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Challenge: Existing methods to develop dialogue agents for complex tasks require sparse reward signals.
Approach: They propose a divide-and-conquer approach that exploits the hidden structure of a task . they use subgoals to divide a goal-oriented task into simpler subgoal sets .
Outcome: The proposed approach performs competitively against state-of-the-art methods that require human-defined subgoals.
Toward Annotator Group Bias in Crowdsourcing (2022.acl-long)

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Challenge: Annotator group bias is a common problem in crowdsourcing, but is often overlooked .
Approach: They propose a probabilistic framework to capture annotator group bias using an extended Expectation Maximization algorithm.
Outcome: The proposed model can model annotator group bias over competitive datasets and demonstrate that it is effective over multiple datasets.

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