Papers with unified intermediate representation
GraphQ IR: Unifying the Semantic Parsing of Graph Query Languages with One Intermediate Representation (2022.emnlp-main)
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| Challenge: | Existing approaches to neural semantic parsing are limited by the semantic gap between natural and formal languages. |
| Approach: | They propose a unified intermediate representation for graph query languages, named GraphQ IR, which has a natural-language-like expression that bridges the semantic gap and formally defined syntax that maintains the graph structure. |
| Outcome: | The proposed representation can convert user queries into graphQ IR, which can later be losslessly compiled into various downstream graph query languages. |
Unsupervised Extraction of Dialogue Policies from Conversations (2024.emnlp-main)
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| Challenge: | Large language models (LLMs) are used to extract dialogue policies from conversational data. |
| Approach: | They propose a method for extracting dialogue policies from conversational data using canonical forms and graph traversal algorithms. |
| Outcome: | The proposed method gives conversation designers greater control and improves the process of developing dialogue policies. |