| Challenge: | Existing approaches to parsing are greedy transition-based and globally optimized . however, the decision-making process is based on local information, causing error propagation to subsequent steps. |
| Approach: | They propose hierarchical pointer network parsers and apply them to dependency and sentence-level discourse parsing tasks. |
| Outcome: | The proposed method outperforms existing methods and sets new state-of-the-art methods on benchmark datasets. |
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| Challenge: | Existing approaches to dependency parsing are local and greedy transitionbased . StackPtr parsers use the information of whole sentences and previously derived subtree structures . |
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Transition-based Semantic Dependency Parsing with Pointer Networks (2020.acl-main)
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Joint Multi-Decoder Framework with Hierarchical Pointer Network for Frame Semantic Parsing (2021.findings-acl)
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| Challenge: | Current researches on frame semantic parsing ignore the interactions among subtasks. |
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Left-to-Right Dependency Parsing with Pointer Networks (N19-1)
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| Challenge: | a new algorithm that parses sentences from left to right is simpler than the top-down stack-pointer parser . a graph-based dependency parsing model has been ahead of the curve in terms of accuracy in the past two years . |
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Span-based Hierarchical Semantic Parsing for Task-Oriented Dialog (D19-1)
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Hierarchical Bracketing Encodings Work for Dependency Graphs (2025.emnlp-main)
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| Challenge: | Sequence labeling (SL) is a simple yet effective paradigm for a wide range of natural language problems. |
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A Top-down Neural Architecture towards Text-level Parsing of Discourse Rhetorical Structure (2020.acl-main)
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| Challenge: | Text-level discourse parsing of discourse rhetorical structure (DRS) is a fundamental research topic in natural language processing. |
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Discourse Representation Parsing for Sentences and Documents (P19-1)
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| Challenge: | Experimental results show that our model outperforms competitive baselines by a wide margin. |
| Approach: | They propose a neural model which parses discourse structures of arbitrary length and granularity. |
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Top-down Discourse Parsing via Sequence Labelling (2021.eacl-main)
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| Challenge: | Discourse analysis is a systematic way to understand how texts are segmented hierarchically into discourse units. |
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