Papers by Van Bach Nguyen
Parallel Universes, Parallel Languages: A Comprehensive Study on LLM-based Multilingual Counterfactual Example Generation (2026.acl-long)
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Qianli Wang, Van Bach Nguyen, Yihong Liu, Fedor Splitt, Nils Feldhus, Christin Seifert, Hinrich Schuetze, Sebastian Möller, Vera Schmitt
| Challenge: | Large language models excel at generating English counterfactuals but their effectiveness in generating multilingual counterfacts remains unclear. |
| Approach: | They conduct automatic evaluations on both directly generated and derived counterfactuals in six languages and find that cross-lingual perturbations follow common strategic principles. |
| Outcome: | The proposed models show that translation-based counterfactuals offer higher validity than their directly generated counterparts, but still fall short of matching the quality of the original English counterf actuals. |
How Do LLMs Generate Contrastive Sentiments? A Mechanistic Perspective (2026.eacl-long)
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| Challenge: | Despite extensive research, the mechanisms underlying LLMs' abilities remain poorly understood. |
| Approach: | They propose and validate a mechanistic intervention that transforms the sentiment of a text from positive to negative while making minimal edits. |
| Outcome: | The proposed intervention increases sentiment flip rate without sacrificing minimal changes to text content. |
LLMs for Generating and Evaluating Counterfactuals: A Comprehensive Study (2024.findings-emnlp)
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| Challenge: | Large Language Models (LLMs) have shown remarkable performance in NLP tasks, but their efficacy in generating high-quality CFs remains uncertain. |
| Approach: | They compare LLMs' ability to generate CFs that flip the original label and human CF's. |
| Outcome: | The proposed models generate fluent CFs, but struggle to keep the induced changes minimal. |