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Found 7 papers, 7 papers with code
Fine-tuned LLMs Know More, Hallucinate Less with Few-Shot Sequence-to-Sequence Semantic Parsing over Wikidata
By pairing our semantic parser with GPT-3, we combine verifiable results with qualified GPT-3 guesses to provide useful answers to 96% of the questions in dev.
ThingTalk: An Extensible, Executable Representation Language for Task-Oriented Dialogues
Task-oriented conversational agents rely on semantic parsers to translate natural language to formal representations.
Localizing Open-Ontology QA Semantic Parsers in a Day Using Machine Translation
We propose Semantic Parser Localizer (SPL), a toolkit that leverages Neural Machine Translation (NMT) systems to localize a semantic parser for a new language.
AutoQA: From Databases To QA Semantic Parsers With Only Synthetic Training Data
To demonstrate the generality of AutoQA, we also apply it to the Overnight dataset.
A Few-Shot Semantic Parser for Wizard-of-Oz Dialogues with the Precise ThingTalk Representation
Previous attempts to build effective semantic parsers for Wizard-of-Oz (WOZ) conversations suffer from the difficulty in acquiring a high-quality, manually annotated training set.
Schema2QA: High-Quality and Low-Cost Q&A Agents for the Structured Web
The key concept is to cover the space of possible compound queries on the database with a large number of in-domain questions synthesized with the help of a corpus of generic query templates.
Genie: A Generator of Natural Language Semantic Parsers for Virtual Assistant Commands
We advocate formalizing the capability of virtual assistants with a Virtual Assistant Programming Language (VAPL) and using a neural semantic parser to translate natural language into VAPL code.
