Papers with formal semantic representation
Semantic Representation for Dialogue Modeling (2021.acl-long)
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| Challenge: | Existing models for dialogue modeling lack ability to represent core semantics, such as ignoring important entities. |
| Approach: | They develop an algorithm to construct dialogue-level AMR graphs from sentence-level data and explore two ways to incorporate AMRs into dialogue modeling. |
| Outcome: | The proposed model is superior to existing models on dialogue understanding and response generation tasks. |
AdaNSP: Uncertainty-driven Adaptive Decoding in Neural Semantic Parsing (P19-1)
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| Challenge: | Semantic parsing (SP) maps a natural language utterance into a formal language . standard Seq2Seq models ignore underlying grammars and may give ill-formed results. |
| Approach: | They propose an end-to-end model for semantic parsing that transduces a natural language sentence to the formal semantic representation. |
| Outcome: | The proposed model outperforms the state-of-the-art models and does not need expertise like predefined grammar or sketches in the meantime. |
Soft Well-Formed Semantic Parsing with Score-Based Selection (2024.lrec-main)
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| Challenge: | Semantic parsing is the task of translating natural language into a structured, formal semantic representation that can be interpreted by machines. |
| Approach: | They propose a score-based method to select well-formed outputs from candidates generated by beam search algorithms. |
| Outcome: | The proposed method reduces the number of ill-formed outputs and improves F1 scores in English. |