arXiv AI August 28, 2026 By Kunjesh Parekh, Anil Kumar Tiwari, Divya Saxena

CIFQA: A Deterministic Tool-Grounded Multi-Agent LLM Framework for Financial Query Answering

CIFQA is a deterministic, tool‑grounded multi‑agent framework that separates language understanding from numerical execution for financial question answering. It assigns specialized agents for interpretation, routing, parameter extraction, computation planning, and response generation, while deterministic Python tools perform the calculations. On a fixed‑deposit benchmark, CIFQA achieves 95.54% accuracy on calculation‑intensive queries and 90.87% overall, outperforming larger LLM baselines and showing that architecture, not scale, drives numerical reliability.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

arXiv AI

Jul 7

Agentic Retrieval-Augmented Generation for Financial Document Question Answering

arXiv:2605. 05409v2 Announce Type: replace Abstract: Financial document question answering (QA) demands complex multi-step numerical reasoning over heterogeneous evidence--structured tables, textual narratives, and footnotes--scattered across corporate filings.

By Yang Shu, Yingmin Liu, Zequn Xie

llms rag agents nlp benchmarks

arXiv AI

Jul 23

FORCE-Bench: A Benchmark, Dataset, and Evaluation Harness for Agentic AI in Enterprise Finance

arXiv:2607. 19409v1 Announce Type: new Abstract: Recent advances in large language models have accelerated deployment of agentic systems in operational finance.

By Wolfgang M. Pauli, Sarah Panda, Kidus Admassu, Said Bleik, Ademola Okerinde, Jeremy Reynolds

llms agents benchmarks safety

arXiv AI

Jun 4

FinTradeBench: A Financial Reasoning Benchmark for LLMs

arXiv:2603. 19225v3 Announce Type: replace-cross Abstract: Real-world financial decision-making is a challenging problem that requires reasoning over heterogeneous signals, including company fundamentals derived from regulatory filings and trading signals computed from price dynamics.

By Yogesh Agrawal, Aniruddha Dutta, Md Mahadi Hasan, Santu Karmaker, Aritra Dutta

llms rag benchmarks safety

arXiv AI

Jul 28

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

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.

By Justice Ayela, Kabir Sahni

llms rag nlp benchmarks

Hugging Face Trending Papers

Jun 22

IPO Finance Agent: Evaluation of LLM Financial Analysts beyond Finance Agent v2, with Automated Rubric Generation -- the Case of the SpaceX (SPCX) IPO

Finance Agent v2 (by Vals AI) has emerged as the reference benchmark for evaluating both Anthropic Claude and OpenAI ChatGPT frontier language models on financial tasks. However, it narrowly deals with periodic reporting from publicly traded companies (SEC 10-K and 10-Q filings), and its agentic harness relies on naive, unenriched chunk retrieval.

llms agents benchmarks safety

arXiv AI

Aug 12

V-FiLLM: Verified Financial LLM Reasoning Benchmark

arXiv:2608. 11047v1 Announce Type: new Abstract: While existing benchmarks have made substantial progress in evaluating LLMs across STEM domains, financial reasoning over structured data remains comparatively less explored.

By Alicia Larsen, Victoire Laurent, Aulia Kharis Rakhamsari, Lara Turgut, Nino Antulov-Fantulin

llms fine-tuning benchmarks safety

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Agentic Retrieval-Augmented Generation for Financial Document Question Answering

FORCE-Bench: A Benchmark, Dataset, and Evaluation Harness for Agentic AI in Enterprise Finance

FinTradeBench: A Financial Reasoning Benchmark for LLMs

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

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V-FiLLM: Verified Financial LLM Reasoning Benchmark