| Challenge: | Renewed interest in semantic analysis has led to a surge of proposed new frameworks . many of these efforts are limited to the analysis of English, but with a number of exceptions e.g., recent efforts in Minimal Recursion Semantics (MRS) and multilingual FrameNet annotation and parsing. |
| Approach: | They propose a cross-lingual decompositional semantic analysis task based on a target language . they propose 'end-to-end' model with an annotating mechanism that supports intra-sentential coreference . |
| Outcome: | The proposed model outperforms baselines by at least 1.75 F1 score on an evaluation dataset. |
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| Challenge: | Existing methods to summarize documents in multiple languages are not systematically evaluated to ensure semantic coherence across target languages. |
| Approach: | They propose a principled re-ranking approach to ensure semantic coherence in documents in multiple target languages while ensuring semantic similarity across target languages. |
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Cross-lingual Text-to-SQL Semantic Parsing with Representation Mixup (2022.findings-emnlp)
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| Challenge: | Experimental results show that Rex can benefit from cross-lingual training and improve the effectiveness of semantic parsers. |
| Approach: | They propose a Representation Mixup Framework for effectively exploiting translations in the cross-lingual Text-to-SQL task. |
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Project-then-Transfer: Effective Two-stage Cross-lingual Transfer for Semantic Dependency Parsing (2021.eacl-main)
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| Challenge: | Several remarkable contributions have been made in syntactic dependency parsing, especially on universal dependencies. |
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A Tour of Explicit Multilingual Semantics: Word Sense Disambiguation, Semantic Role Labeling and Semantic Parsing (2022.aacl-tutorials)
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| Challenge: | a recent advent of pretrained language models has sparked a revolution in NLP . but, there are still questions about whether current approaches capture explicit, symbolic meaning . this tutorial will review efforts to tackle three key open problems in lexical and sentence-level semantics . |
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A Survey on Cross-Lingual Summarization (2022.tacl-1)
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| Challenge: | Cross-lingual summarization is a task of generating a summary in one language for a given document in a different language. |
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Context Dependent Semantic Parsing: A Survey (2020.coling-main)
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| Challenge: | Semantic parsing is the task of translating natural language utterances into machine-readable meaning representations. |
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Understanding Cross-Lingual Alignment—A Survey (2024.findings-acl)
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| Challenge: | Cross-lingual alignment is the meaningful similarity of representations across languages in multilingual language models. |
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Universal Decompositional Semantic Parsing (2020.acl-main)
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| Challenge: | Decompositional Semantics is a formalism that encodes semantic information in a feature-based scheme using continuous scales rather than categorical labels. |
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Zero-Shot Cross-lingual Semantic Parsing (2022.acl-long)
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| Challenge: | Recent work in cross-lingual semantic parsing assumes access to high-quality machine translation systems and word alignment tools. |
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Revisiting Cross-Lingual Summarization: A Corpus-based Study and A New Benchmark with Improved Annotation (2023.acl-long)
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Yulong Chen, Huajian Zhang, Yijie Zhou, Xuefeng Bai, Yueguan Wang, Ming Zhong, Jianhao Yan, Yafu Li, Judy Li, Xianchao Zhu, Yue Zhang
| Challenge: | Existing work on cross-lingual summarization (CLS) does not consider crosslingual sources for summarizing. |
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