| Challenge: | Generic deep realizers are used for natural language generation, but they are not yet fully dominated by statistical or neuronal methods. |
| Approach: | They propose a generic deep realizer that produces syntactic dependency structures in languages . they use a graph transducer to lexicalize multiword expressions and build on it . |
| Outcome: | The proposed system produces syntactic dependency structures in English, French, Lithuanian and Persian . it is generic in that it is designed to operate across a wide range of languages and applications . |
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| Challenge: | GenDR is a text realizer that takes as input a graph-based semantic representation and outputs the corresponding syntactic dependency trees. |
| Approach: | They propose to use a dictionary that maps semantemes to corresponding lexical units in a given language to perform a task in lexiconalization. |
| Outcome: | The proposed module can build a rich semantic dictionary for French. |
A Broad-Coverage Deep Semantic Lexicon for Verbs (2020.lrec-1)
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| Challenge: | a lack of a broad-coverage deep semantic lexicon hinders deep language understanding . we have developed a resource for verbs with the coverage of WordNet and syntactic and semantic details . |
| Approach: | They propose a deep lexical resource for verbs with the coverage of WordNet and syntactic and semantic details that meet or exceed existing resources. |
| Outcome: | The proposed resource has the coverage of WordNet and syntactic and semantic details that exceed existing resources. |
Massively Multilingual Lexical Specialization of Multilingual Transformers (2023.acl-long)
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| Challenge: | Existing work focused on lexical specialization of monolingual PLMs with immense quantities of monolinguistic constraints, but recent work shows that pretrained language models can be rewired to produce high-quality word representations and perform type-level lexicals. |
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LexFit: Lexical Fine-Tuning of Pretrained Language Models (2021.acl-long)
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| Challenge: | Transformer-based language models implicitly store a wealth of lexical semantic knowledge, but it is non-trivial to extract that knowledge effectively from their parameters. |
| Approach: | They propose to expose and enrich lexical knowledge from transformer-based language models to serve as effective decontextualized word encoders even when fed input words "in isolation" |
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Translation-based Lexicalization Generation and Lexical Gap Detection: Application to Kinship Terms (2024.acl-long)
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| Challenge: | Existing methods for identifying lexical gaps have been limited . kinship terms are well-suited for investigations into lexicons and lexicals . |
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Recursive Context-Aware Lexical Simplification (D19-1)
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| Challenge: | REC-LS is a system that can be used to perform a number of simplifications at once, but the results are sometimes ungrammatical and meaning can be changed, making the original text less clear and more complex. |
| Approach: | They propose a recursive context-aware lexical simplification architecture that takes previous simplification steps into account and makes use of the wider context when detecting the words in need of simplification. |
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Lexi: A tool for adaptive, personalized text simplification (C18-1)
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| Challenge: | Existing research on text simplification has aimed to develop generic solutions . instead, we need to develop customized simplification systems for individual users . |
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Probing Pretrained Language Models for Lexical Semantics (2020.emnlp-main)
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| Challenge: | Existing studies have focused on morphosyntactic, semantic, and world knowledge, but it remains unclear to what extent LMs derive lexical type-level knowledge from words in context. |
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Creating a Verb Synonym Lexicon Based on a Parallel Corpus (L18-1)
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| Challenge: | a new lexical resource called CzEngClass is being built to help define synonyms in a bilingual context. |
| Approach: | They propose to group verb senses into bilingual verbal synonym groups and use a parallel dependency corpus to explore semantic 'equivalence' they argue that existence of core argument mappings and adjunct mappings to a common set of semantic roles is a suitable criterion for a reasonable verb synonymy definition . |
| Outcome: | The proposed resource will be available by mid-2018 . |
The impact of lexical and grammatical processing on generating code from natural language (2022.findings-acl)
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| Challenge: | Yin and Neubig (2018) identify four key components of importance for natural language to code translation. |
| Approach: | They propose a seq2seq-based architecture that relies on a grammar-based decoder and a lexical substitution component for natural language to code translation. |
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