mlsanityData to 7 Oct 2026

FLANS at SemEval-2026 Task 7: RAG with Open-Sourced Smaller LLMs for Everyday Knowledge Across Diverse Languages and Cultures

arXiv 2603.01910 ↗First posted 2 Mar 2026cs.CL cs.AIcited by 1

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Abstract (arXiv)

This system paper describes our participation in the SemEval-2025 Task-7 ``Everyday Knowledge Across Diverse Languages and Cultures''. We attended two subtasks, i.e., Track 1: Short Answer Questions (SAQ), and Track 2: Multiple-Choice Questions (MCQ). The methods we used are retrieval augmented generation (RAGs) with open-sourced smaller LLMs (OS-sLLMs). To better adapt to this shared task, we created our own culturally aware knowledge base (CulKBs) by extracting Wikipedia content using keyword lists we prepared. We extracted both culturally-aware wiki-text and country-specific wiki-summary. In addition to the local CulKBs, we also have one system integrating live online search output via DuckDuckGo. Towards better privacy and sustainability, we aimed to deploy smaller LLMs (sLLMs) that are open-sourced on the Ollama platform. We share the prompts we developed using refinement techniques and report the learning curve of such prompts. The tested languages are English, Spanish, and Chinese for both tracks. Our resources and codes are shared via https://github.com/aaronlifenghan/FLANS-2026

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 8 of its 17 references that are in the map. First posted on arXiv 2 Mar 2026.

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8 of 17 references.

References · 8

  1. 2020Scaling Laws for Neural Language Modelscited by 6,411
  2. 2019Energy and Policy Considerations for Deep Learning in NLPcited by 1,242
  3. 2019TinyBERT: Distilling BERT for Natural Language Understandingcited by 1,153
  4. 2024BLEnD: A Benchmark for LLMs on Everyday Knowledge in Diverse Cultures and Languagescited by 171
  5. 2024Multilingual Retrieval Augmented Generation for Culturally-Sensitive Tasks: A Benchmark for Cross-lingual Robustnesscited by 13
  6. 2024Improving LLM Reliability with RAG in Religious Question-Answering: MufassirQAScited by 6
  7. 2025MaLei at MultiClinSUM: Summarisation of Clinical Documents using Perspective-Aware Iterative Self-Prompting with LLMscited by 6
  8. 2025CultureSynth: A Hierarchical Taxonomy-Guided and Retrieval-Augmented Framework for Cultural Question-Answer Synthesiscited by 6

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026SEA-NLI: Natural Language Inference as a Lens into Southeast Asian Cultural Understandingcited by 0

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  1. 2026Knowledge-Graph Based Augmentation versus Retrieval Augmented Generation for Cultural-Related Question Answering
  2. 2024NativQA: Multilingual Culturally-Aligned Natural Query for LLMs
  3. 2025NativQA Framework: Enabling LLMs and VLMs with Native, Local, and Everyday Knowledge
  4. 2025Know Or Not: a library for evaluating out-of-knowledge base robustness
  5. 2025On the Consistency of Multilingual Context Utilization in Retrieval-Augmented Generation
  6. 2023DIVKNOWQA: Assessing the Reasoning Ability of LLMs via Open-Domain Question Answering over Knowledge Base and Text
  7. 2024Enhancing Multilingual Information Retrieval in Mixed Human Resources Environments: A RAG Model Implementation for Multicultural Enterprise
  8. 2026Simorgh at SemEval-2026 task 7: Region-Aware Hybrid Retrieval for Low-Resource Cultural Reasoning in Multilingual Question Answering