Papers with rule based memory scheduling policies

1 papers
Episodic Memory Reader: Learning What to Remember for Question Answering from Streaming Data (P19-1)

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Challenge: Existing QA methods lack scalability and performance is difficult to solve with document-level contexts.
Approach: They propose an end-to-end deep network model that sequentially reads the input contexts into an external memory while replacing memories that are less important for answering unseen questions.
Outcome: The proposed model improves on a synthetic dataset and real-world large-scale textual and video QA datasets.

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