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Found 5 papers, 1 papers with code
Improving Cross-Domain Low-Resource Text Generation through LLM Post-Editing: A Programmer-Interpreter Approach
Post-editing has proven effective in improving the quality of text generated by large language models (LLMs) such as GPT-3. 5 or GPT-4, particularly when direct updating of their parameters to enhance text quality is infeasible or expensive.
Reranking for Natural Language Generation from Logical Forms: A Study based on Large Language Models
Our approach involves initially generating a set of candidate outputs by prompting an LLM and subsequently reranking them using a task-specific reranker model.
Foundations of Collaborative Task-Oriented Dialogue: What's in a Slot?
In this paper, we examine the foundations of task-oriented dialogues, in which systems are requested to perform tasks for humans.
Active learning for deep semantic parsing
Semantic parsing requires training data that is expensive and slow to collect.
Multilingual Semantic Parsing And Code-Switching
As far as we know, this is the first study of code-switching in semantic parsing.
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