Language-Routed RAG and Direct Option Scoring for Multilingual Financial QA: DS@GT at FinMMEval 文章

ArXiv CS.CL2026-07-28PAPERen作者: Justice Ayela, Kabir Sahni

详细信息

来源站点
ArXiv CS.CL
作者
Justice Ayela, Kabir Sahni
文章类型
PAPER
语言
en
发布日期
2026-07-28

摘要

arXiv:2607.22841v1 Announce Type: cross Abstract: We present DS@GT's submission to FinMMEval 2026 Task 1, a multilingual financial exam question answering benchmark spanning English, Spanish, Greek, Chinese, and Hindi. Financial certification exams such as the CFA, EFPA, and CPA demand structured domain reasoning that standard NLP benchmarks do not capture, and this challenge compounds across languages where retrieval and representation infrastructure is underdeveloped. We build a retrieval-augmented pipeline on LangGraph that detects query language and retrieves semantically relevant exemplars from a 30,209-entry multilingual knowledge base using BGE-M3 embeddings and FAISS indexing. The system then scores answers via Retrieval-Augmented Direct Scoring (RADS), reading next-token log-probabilities over candidate option letters rather than generating free-form output.

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