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02/02/2022
Retrieve-and-Fill for Scenario-based Task-Oriented Semantic Parsing
Task-oriented semantic parsing models have achieved strong results in re...
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07/10/2021
Assessing Data Efficiency in Task-Oriented Semantic Parsing
Data efficiency, despite being an attractive characteristic, is often ch...
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05/27/2021
Diagnosing Transformers in Task-Oriented Semantic Parsing
Modern task-oriented semantic parsing approaches typically use seq2seq t...
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04/15/2021
Span Pointer Networks for Non-Autoregressive Task-Oriented Semantic Parsing
An effective recipe for building seq2seq, non-autoregressive, task-orien...
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04/15/2021
Low-Resource Task-Oriented Semantic Parsing via Intrinsic Modeling
Task-oriented semantic parsing models typically have high resource requi...
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10/15/2020
Compressive Summarization with Plausibility and Salience Modeling
Compressive summarization systems typically rely on a crafted set of syn...
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10/15/2020
Understanding Neural Abstractive Summarization Models via Uncertainty
An advantage of seq2seq abstractive summarization models is that they ge...
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06/05/2020
Accelerating Natural Language Understanding in Task-Oriented Dialog
Task-oriented dialog models typically leverage complex neural architectu...
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04/29/2020
Detecting Perceived Emotions in Hurricane Disasters
Natural disasters (e.g., hurricanes) affect millions of people each year...
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03/17/2020
Calibration of Pre-trained Transformers
Pre-trained Transformers are now ubiquitous in natural language processi...
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02/04/2020
Lightweight Convolutional Representations for On-Device Natural Language Processing
The increasing computational and memory complexities of deep neural netw...
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10/28/2019
Evaluating Lottery Tickets Under Distributional Shifts
The Lottery Ticket Hypothesis suggests large, over-parameterized neural ...
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10/28/2019