A Unified Generative Framework for Bilingual Euphemism Detection and Identification (2024.findings-acl)
Copied to clipboard
| Challenge: | Existing euphemism datasets are only domain-specific or language-specific. |
| Approach: | They propose a unified model to jointly conduct bilingual euphemism detection and identification tasks. |
| Outcome: | The proposed model is effective and provides a new reference standard for euphemism detection and identification. |
Similar Papers
Towards a unified framework for bilingual terminology extraction of single-word and multi-word terms (C18-1)
Copied to clipboard
| Challenge: | Existing methods for extracting bilingual terminology from comparable corpora are limited to a set of syntactic patterns. |
| Approach: | They propose a framework for aligning bilingual terms independently of term lengths . they introduce some enhancements to the context-based and neural network based approaches . |
| Outcome: | The proposed framework improves the performance of the context-based and neural network based approaches and can be adapted in specialized domains. |
Euphemistic Phrase Detection by Masked Language Model (2021.findings-emnlp)
Copied to clipboard
| Challenge: | euphemisms are ordinary-sounding words with a secret meaning that are used to conceal information . a primary motive of their use on social media is to evade content moderation efforts . |
| Approach: | They propose to use social media to detect euphemisms without human effort . they first perform phrase mining on a raw text corpus to extract quality phrases . then they use word embedding similarities to select a set of euphoristic phrase candidates . |
| Outcome: | The proposed algorithm shows 20-50% higher detection accuracies than baselines. |
MEDs for PETs: Multilingual Euphemism Disambiguation for Potentially Euphemistic Terms (2024.findings-eacl)
Copied to clipboard
Patrick Lee, Alain Chirino Trujillo, Diana Cuevas Plancarte, Olumide Ojo, Xinyi Liu, Iyanuoluwa Shode, Yuan Zhao, Anna Feldman, Jing Peng
| Challenge: | Euphemisms are a linguistic device used to soften or neutralize language that may otherwise be harsh or awkward to state directly. |
| Approach: | They train a multilingual transformer model to disambiguate potentially euphemistic terms in multilingual and cross-lingual settings. |
| Outcome: | The proposed model performs better than monolingual models on the disambiguation task compared to monolingual ones in multilingual and cross-lingual settings. |
How Universal are Universal Dependencies? Exploiting Syntax for Multilingual Clause-level Sentiment Detection (2020.lrec-1)
Copied to clipboard
| Challenge: | a new method for clause-level sentiment detection is proposed for multilingual use cases. |
| Approach: | They propose a pipeline method that makes the most of syntactic structures based on Universal Dependencies. |
| Outcome: | The proposed method achieves high precision in sentiment detection for 17 languages . it avoids machine-learning approaches that may cause obstacles to its use cases . |
UnifiedGEC: Integrating Grammatical Error Correction Approaches for Multi-languages with a Unified Framework (2025.coling-demos)
Copied to clipboard
| Challenge: | Existing tools for GEC have been developed to support research on grammatical errors, but there is no comprehensive evaluation on these models. |
| Approach: | They propose an open-source framework for Grammatical Error Correction that integrates 5 widely-used GEC models and compares their performance on 7 datasets in different languages. |
| Outcome: | The proposed framework compares 5 widely-used models on 7 datasets in different languages. |
Data Augmentation for Hypernymy Detection (2021.eacl-main)
Copied to clipboard
| Challenge: | Existing methods for supervised inference have limited quality training data. |
| Approach: | They propose two techniques which generate new training examples from existing ones . they combine linguistic principles of hypernym transitivity and intersective modifier-noun composition . |
| Outcome: | The proposed techniques generate new training examples from existing datasets. |
Thesis Proposal: Targeted and Unified Cross-Lingual Unlearning from Multilingual Language Models (2026.acl-srw)
Copied to clipboard
| Challenge: | Large language models trained on corpora scraped from the web can reproduce sensitive and copyright-protected data. |
| Approach: | They propose to extend existing benchmarks to multilingual data by compiling parallel translations of question-answer pairs consisting of real-world facts and synthetic personally identifiable information. |
| Outcome: | The proposed dataset will include translations of question-answer pairs consisting of real-world facts and synthetic personally identifiable information. |
A Hybrid Detection and Generation Framework with Separate Encoders for Event Extraction (2023.eacl-main)
Copied to clipboard
| Challenge: | Recent work on event extraction tasks has been based on classification-based methods . a new generation-based method is being developed to extract event triggers and event arguments from plain text. |
| Approach: | They propose to use independent encoders to model event detection and event argument extraction, respectively, and use token-level features to precisely control the fusion between two encoder. |
| Outcome: | The proposed method avoids feature interference and achieves joint training . it is compared with other methods and achieved competitive results on standard benchmarks . |
Towards Unified Task Embeddings Across Multiple Models: Bridging the Gap for Prompt-Based Large Language Models and Beyond (2024.findings-acl)
Copied to clipboard
| Challenge: | Existing task embedding methods rely on fine-tuned, task-specific language models, which hinders their adaptability to prompt-guided Large Language Models (LLMs). |
| Approach: | They propose a framework for unified task embedding that harmonizes task embeds from various models within a single vector space. |
| Outcome: | The proposed framework harmonizes task embeddings from various models within a single vector space. |
A Joint Matrix Factorization Analysis of Multilingual Representations (2023.findings-emnlp)
Copied to clipboard
| Challenge: | Existing studies have demonstrated that pre-trained models acquire and incorporate linguistic knowledge in their multilingual representations. |
| Approach: | They propose a tool for comparing latent representations of multilingual and monolingual models . they use joint matrix factorization to analyze multiple sets of representations in a joint manner . |
| Outcome: | The proposed tool analyzes latent representations of multilingual and monolingual models . it shows that language properties influence the factorization outputs . |