12,260 research outputs found
A Context-aware Attention Network for Interactive Question Answering
Neural network based sequence-to-sequence models in an encoder-decoder
framework have been successfully applied to solve Question Answering (QA)
problems, predicting answers from statements and questions. However, almost all
previous models have failed to consider detailed context information and
unknown states under which systems do not have enough information to answer
given questions. These scenarios with incomplete or ambiguous information are
very common in the setting of Interactive Question Answering (IQA). To address
this challenge, we develop a novel model, employing context-dependent
word-level attention for more accurate statement representations and
question-guided sentence-level attention for better context modeling. We also
generate unique IQA datasets to test our model, which will be made publicly
available. Employing these attention mechanisms, our model accurately
understands when it can output an answer or when it requires generating a
supplementary question for additional input depending on different contexts.
When available, user's feedback is encoded and directly applied to update
sentence-level attention to infer an answer. Extensive experiments on QA and
IQA datasets quantitatively demonstrate the effectiveness of our model with
significant improvement over state-of-the-art conventional QA models.Comment: 9 page
Is children's reading “good enough”? Links between online processing and comprehension as children read syntactically ambiguous sentences
We monitored 8- and 10-year-old children’s eye movements as they read sentences containing a temporary syntactic ambiguity to obtain a detailed record of their online processing. Children showed the classic garden-path effect in online processing. Their reading was disrupted following disambiguation, relative to control sentences containing a comma to block the ambiguity, although the disruption occurred somewhat later than would be expected for mature readers. We also asked children questions
to probe their comprehension of the syntactic ambiguity offline. They made more errors following ambiguous sentences than following control sentences, demonstrating that the initial incorrect parse of the garden-path sentence influenced offline comprehension. These findings are consistent with “good enough” processing effects seen in adults. While faster reading times and more regressions were generally associated with better comprehension, spending longer reading the question predicted comprehension success specifically in the ambiguous condition. This suggests that reading the question prompted children to reconstruct the sentence and engage in some form of processing, which in turn
increased the likelihood of comprehension success. Older children were more sensitive to the syntactic function of commas, and, overall, they were faster and more accurate than younger children
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