How Far are We from Effective Context Modeling? An Exploratory Study on Semantic Parsing in Context
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Abstract (arXiv)
Recently semantic parsing in context has received considerable attention, which is challenging since there are complex contextual phenomena. Previous works verified their proposed methods in limited scenarios, which motivates us to conduct an exploratory study on context modeling methods under real-world semantic parsing in context. We present a grammar-based decoding semantic parser and adapt typical context modeling methods on top of it. We evaluate 13 context modeling methods on two large complex cross-domain datasets, and our best model achieves state-of-the-art performances on both datasets with significant improvements. Furthermore, we summarize the most frequent contextual phenomena, with a fine-grained analysis on representative models, which may shed light on potential research directions. Our code is available at https://github.com/microsoft/ContextualSP.
Key facts. Cited by 53 papers in the map (data through 7 Oct 2026). First posted on arXiv 3 Feb 2020.
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Citing papers per year: 2021: 13; 2022: 14; 2023: 14; 2024: 11; 2025: 1.
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- 2024In-context Contrastive Learning for Event Causality Identification17 May 2024
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