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

HFEPX Relevance Assessment

This paper is adjacent to HFEPX scope and is best used for background context, not as a primary protocol reference.

Field Provenance & Confidence

Each key protocol field shows extraction state, confidence band, and data source so you can decide whether to trust it directly or validate from full text.

Protocol And Measurement Signals

This system paper describes our participation in the SemEval-2025 Task-7 ``Everyday Knowledge Across Diverse Languages and Cultures''. HFEPX protocol signal is limited in abstract-level metadata, so treat it as adjacent context. Updated from current HFEPX corpus.

Generated Mar 8, 2026, 7:52 AM · Grounded in abstract + metadata only

Research Summary

Contribution Summary

• 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).

Why It Matters For Eval

• Abstract shows limited direct human-feedback or evaluation-protocol detail; use as adjacent methodological context.

Researcher Checklist

• Gap: Human feedback protocol is explicit

  No explicit human feedback protocol detected.

• Gap: Evaluation mode is explicit

  No clear evaluation mode extracted.

• Gap: Quality control reporting appears

  No calibration/adjudication/IAA control explicitly detected.

• Pass: Benchmark or dataset anchors are present

  Detected: Semeval

• Gap: Metric reporting is present

  No metric terms extracted.

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