mlsanityData to 14 Oct 2026

Evaluating Cultural Knowledge Processing in Large Language Models: A Cognitive Benchmarking Framework Integrating Retrieval-Augmented Generation

arXiv 2511.01649 ↗First posted 3 Nov 2025cs.CLcited by 0

On the map: Retrieval-augmented generation → Generation and context integration

Abstract (arXiv)

This study proposes a cognitive benchmarking framework to evaluate how large language models (LLMs) process and apply culturally specific knowledge. The framework integrates Bloom's Taxonomy with Retrieval-Augmented Generation (RAG) to assess model performance across six hierarchical cognitive domains: Remembering, Understanding, Applying, Analyzing, Evaluating, and Creating. Using a curated Taiwanese Hakka digital cultural archive as the primary testbed, the evaluation measures LLM-generated responses' semantic accuracy and cultural relevance.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Generation and context integration, one of 15 directions in Retrieval-augmented generation. Builds on 23 of its 48 references that are in the map. First posted on arXiv 3 Nov 2025.

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23 of 48 references.

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  1. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks22 May

Other references · 22

  1. 2020Measuring Massive Multitask Language Understandingcited by 7,963
  2. 2023Retrieval-Augmented Generation for Large Language Models: A Surveycited by 2,212
  3. 2018Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarizationcited by 1,317
  4. 2023A Survey on Evaluation of Large Language Modelscited by 1,242
  5. 2024Retrieval-Augmented Generation for AI-Generated Content: A Surveycited by 354
  6. 2023S3: Social-network Simulation System with Large Language Model-Empowered Agentscited by 233
  7. 2023Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Biascited by 232
  8. 2023LawBench: Benchmarking Legal Knowledge of Large Language Modelscited by 117
  9. 2024A Survey on Retrieval-Augmented Text Generation for Large Language Modelscited by 77
  10. 2025We're Different, We're the Same: Creative Homogeneity Across LLMscited by 42
  11. 2021The future of human-AI collaboration: a taxonomy of design knowledge for hybrid intelligence systemscited by 39
  12. 2024Assessing and Understanding Creativity in Large Language Modelscited by 35
10 more
  1. 2024AI Hallucinations: A Misnomer Worth Clarifyingcited by 34
  2. 2023MLLM-Bench: Evaluating Multimodal LLMs with Per-sample Criteriacited by 27
  3. 2024Leveraging Large Language Models for Learning Complex Legal Concepts through Storytellingcited by 23
  4. 2024Evaluating Creative Short Story Generation in Humans and Large Language Modelscited by 21
  5. 2024Re-TASK: Revisiting LLM Tasks from Capability, Skill, and Knowledge Perspectivescited by 13
  6. 2024TransportationGames: Benchmarking Transportation Knowledge of (Multimodal) Large Language Modelscited by 8
  7. 2025Assessing AI-Generated Questions' Alignment with Cognitive Frameworks in Educational Assessmentcited by 8
  8. 2024COGNET-MD, an evaluation framework and dataset for Large Language Model benchmarks in the medical domaincited by 4
  9. 2023Rethinking the Evaluating Framework for Natural Language Understanding in AI Systems: Language Acquisition as a Core for Future Metricscited by 2
  10. 2025Large Language Models for Oral History Understanding with Text Classification and Sentiment Analysiscited by 2

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  1. 2024Benchmarking Cognitive Domains for LLMs: Insights from Taiwanese Hakka Culture
  2. 2025Towards Geo-Culturally Grounded LLM Generations
  3. 2026Knowledge-Graph Based Augmentation versus Retrieval Augmented Generation for Cultural-Related Question Answering
  4. 2025CultureSynth: A Hierarchical Taxonomy-Guided and Retrieval-Augmented Framework for Cultural Question-Answer Synthesis
  5. 2026Injecting Knowledge from Social Science Journals to Improve Indonesian Cultural Understanding by LLMs
  6. 2025RAVENEA: A Benchmark for Multimodal Retrieval-Augmented Visual Culture Understanding
  7. 2025CulTrace: Tracing Internal Cultural Reasoning in Large Language Models
  8. 2025CURE: Cultural Understanding and Reasoning Evaluation - A Framework for "Thick" Culture Alignment Evaluation in LLMs