arXiv AI
FinInteract: Benchmarking Clarification and Intent Integration in Ambiguous Financial Question Answering
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arXiv AI
Sep 4
Enhancing Financial Question Answering: A Novel Benchmark Dataset of Banks' financial statements
FinRAG-QA is a new benchmark dataset for financial question answering, featuring 999 practitioner-curated questions on 10 standardised indicators drawn from 209 annual and Pillar 3 reports of 24 major European and U.S. banks between 2019 and 2023. The dataset focuses on cross‑institutional retrieval over documents averaging 198k words, making it longer than any existing financial QA resource. Experiments on a multi‑stage Retrieval‑Augmented Generation pipeline show that contextual chunk enrichment and a retrieval‑optimised embedding model significantly improve NDCG@10, while a reasoning‑optimised generator boosts answer accuracy from 44.6% to 79.0% when the correct document is retrieved.
arXiv AI
Jun 12
Fin-RATE: A Real-world Financial Analytics and Tracking Evaluation Benchmark for LLMs on SEC Filings
arXiv:2602. 07294v4 Announce Type: replace-cross Abstract: With the increasing deployment of Large Language Models (LLMs) in the finance domain, LLMs are increasingly expected to parse complex regulatory disclosures.
arXiv AI
Sep 10
IGT @ FinMMEval 2026 Task 2: Question-Type Prompting with Targeted Extraction for Multilingual Financial QA
The IGT system tackles PolyFiQA Task 2 of the FinMMEval Lab, a multilingual financial QA challenge involving English SEC filings and news in five languages. It distinguishes two question families: numeric‑structured queries are answered via keyword extraction from filings, while synthesis queries use rule‑based passage selection from news. The approach yields a development ROUGE‑1 of ~0.395, a 60% boost over a generic RAG baseline, and places third among twelve teams on the official test set.
arXiv Computation and Language
Sep 23
FinFIRST: Benchmarking Search Agents for Financial Information Retrieval, Sourcing and Traceability
arXiv:2609.25192v1 Announce Type: new Abstract: Financial search is a highly demanding task for LLM agents, requiring not only a correct final answer but also temporally valid information retrieval,...
arXiv AI
Aug 11
Can Open-Weight Models Compete on Financial Text Comprehension?
arXiv:2608. 08634v1 Announce Type: new Abstract: Open-weight language models from Chinese AI labs caught up on benchmarks relative to proprietary frontier models in recent months.
arXiv AI
Aug 6
FinReportBench: Measuring and Improving Institution-Grade Financial Report Generation
arXiv:2608. 04374v1 Announce Type: cross Abstract: Large language models can produce fluent financial analysis, but fluency alone does not establish whether a report is suitable for institutional delivery.