3 citations · 6 across the 4 of their papers we have counts for
4 papers
PIZZA: A new benchmark for complex end-to-end task-oriented parsing
Konstantine Arkoudas, Nicolas Guenon des Mesnards, Melanie Rubino +4
Much recent work in task-oriented parsing has focused on finding a middle ground between flat slots and intents, which are inexpressive but easy to annotate, and powerful represent…
Cross-TOP: Zero-Shot Cross-Schema Task-Oriented Parsing
Melanie Rubino, Nicolas Guenon des Mesnards, Uday Shah +3
Deep learning methods have enabled task-oriented semantic parsing of increasingly complex utterances. However, a single model is still typically trained and deployed for each task…
Training Naturalized Semantic Parsers with Very Little Data
Subendhu Rongali, Konstantine Arkoudas, Melanie Rubino +1
Semantic parsing is an important NLP problem, particularly for voice assistants such as Alexa and Google Assistant. State-of-the-art (SOTA) semantic parsers are seq2seq architectur…
Unfreeze with Care: Space-Efficient Fine-Tuning of Semantic Parsing Models
Weiqi Sun, Haidar Khan, Nicolas Guenon des Mesnards +2
Semantic parsing is a key NLP task that maps natural language to structured meaning representations. As in many other NLP tasks, SOTA performance in semantic parsing is now attaine…