16 citations · 48 across the 11 of their papers we have counts for
7 papers · 1 filter
AutoNLU: Detecting, root-causing, and fixing NLU model errors
Pooja Sethi, Denis Savenkov, Forough Arabshahi +6
Improving the quality of Natural Language Understanding (NLU) models, and more specifically, task-oriented semantic parsing models, in production is a cumbersome task. In this work…
Assessing Data Efficiency in Task-Oriented Semantic Parsing
Shrey Desai, Akshat Shrivastava, Justin Rill +4
Data efficiency, despite being an attractive characteristic, is often challenging to measure and optimize for in task-oriented semantic parsing; unlike exact match, it can require…
Latency-Aware Neural Architecture Search with Multi-Objective Bayesian Optimization
David Eriksson, Pierce I-Jen Chuang, Samuel Daulton +7
When tuning the architecture and hyperparameters of large machine learning models for on-device deployment, it is desirable to understand the optimal trade-offs between on-device l…
Diagnosing Transformers in Task-Oriented Semantic Parsing
Shrey Desai, Ahmed Aly
Modern task-oriented semantic parsing approaches typically use seq2seq transformers to map textual utterances to semantic frames comprised of intents and slots. While these models…
Low-Resource Task-Oriented Semantic Parsing via Intrinsic Modeling
Shrey Desai, Akshat Shrivastava, Alexander Zotov +1
Task-oriented semantic parsing models typically have high resource requirements: to support new ontologies (i.e., intents and slots), practitioners crowdsource thousands of samples…
Non-Autoregressive Semantic Parsing for Compositional Task-Oriented Dialog
Arun Babu, Akshat Shrivastava, Armen Aghajanyan +3
Semantic parsing using sequence-to-sequence models allows parsing of deeper representations compared to traditional word tagging based models. In spite of these advantages, widespr…
Span Pointer Networks for Non-Autoregressive Task-Oriented Semantic Parsing
Akshat Shrivastava, Pierce Chuang, Arun Babu +4
An effective recipe for building seq2seq, non-autoregressive, task-oriented parsers to map utterances to semantic frames proceeds in three steps: encoding an utterance , predict…