Papers by Ifeoluwa Wuraola

2 papers
SLANG-GraphRAG: Multi-Layered Retrieval with Domain-Specific Knowledge for Low Resource Social Media Conversations (2026.findings-eacl)

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Challenge: Standard NLP benchmarks often miss subtle, culturally-specific cues in social media . incorporating structured cultural knowledge into the retrieval process improves accuracy by up to 31% .
Approach: They propose a retrieval-augmented framework that integrates a culture-specific slang knowledge graph into large language models via one-shot prompting.
Outcome: The proposed framework outperforms traditional and unstructured retrieval methods in slang-based models by 31% and 28%.
Understanding Slang with LLMs: Modelling Cross-Cultural Nuances through Paraphrasing (2024.emnlp-main)

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Challenge: a recent study examines the ability of large language models (LLMs) to paraphrase slang within climate-related tweets . slanted tweets from non-anglocentric countries may contain cultural references and idioms based on sociocultural identities .
Approach: They investigate the ability of large language models to paraphrase slang within climate-related tweets from Nigeria and the UK.
Outcome: The proposed model can paraphrase slang within climate-related tweets from Nigeria and the UK . the model can only parse sexist and sex-related slurs, the study shows .

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