C-Mining automatically mines high-fidelity Culture Points from raw multilingual text by treating cross-lingual geometric isolation in embeddings as a quantifiable signal for cultural specificity, then uses them to synthesize better instruction data.
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NBQ is a plug-and-play framework for adaptive question selection in conversations to produce structured user profiles, with QuickMatch enabling scalable reciprocal matching through approximate vector search.
A multilingual self-consistency plus self-critique method raises cultural alignment scores on English queries by 5.03% on the BLEnD benchmark using only self-generated data.
MEMOed framework attributes LLM generations about cultures to pretraining memorization and finds frequency-based biases across 110 cultures for food and clothing.
SemEval-2026 Task 7 presents a benchmark and two evaluation tracks for assessing LLMs on everyday knowledge in diverse languages and cultures without allowing training on the test data.
citing papers explorer
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C-Mining: Unsupervised Discovery of Seeds for Cultural Data Synthesis via Geometric Misalignment
C-Mining automatically mines high-fidelity Culture Points from raw multilingual text by treating cross-lingual geometric isolation in embeddings as a quantifiable signal for cultural specificity, then uses them to synthesize better instruction data.
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NBQ: Next-Best-Question for Dynamic Profiling
NBQ is a plug-and-play framework for adaptive question selection in conversations to produce structured user profiles, with QuickMatch enabling scalable reciprocal matching through approximate vector search.
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Cross-Lingual Consensus: Aligning Multilingual Cultural Knowledge via Multilingual Self-Consistency
A multilingual self-consistency plus self-critique method raises cultural alignment scores on English queries by 5.03% on the BLEnD benchmark using only self-generated data.
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Attributing Culture-Conditioned Generations to Pretraining Corpora
MEMOed framework attributes LLM generations about cultures to pretraining memorization and finds frequency-based biases across 110 cultures for food and clothing.
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SemEval-2026 Task 7: Everyday Knowledge Across Diverse Languages and Cultures
SemEval-2026 Task 7 presents a benchmark and two evaluation tracks for assessing LLMs on everyday knowledge in diverse languages and cultures without allowing training on the test data.