arXiv AI

Automated Summarization of Financial News Using Large Language Models and Retrieval-Augmented Generation: An Early Empirical Study (Fall 2023)

arXiv:2608. 19526v1 Announce Type: cross Abstract: Stock market analysts and investors face a daily challenge: too much financial news, too little time.

arXiv AI

Jul 13

Augmenting Fundamental Analysis with Large Language Models: A RAG-Based System for Generating Investor Briefs

arXiv:2607. 09121v1 Announce Type: cross Abstract: In this study, we examine the opportunities brought by Large Language Models (LLMs) to various aspects of fundamental analysis of companies based on their reports as well as data and documents describing macroeconomic situation like GDP and inflation changes as well as documents filled to the U.

By Bartosz Zi\'o{\l}ko, Kacper Dobrzeniewski

llms rag

arXiv AI

Jun 17

The Stanford EDGAR Filings Dataset: Reconstructing U.S. Corporate and Financial Disclosures into Layout-Faithful and Token-Efficient Pretraining Data

arXiv:2606. 18192v1 Announce Type: new Abstract: As high-quality public web corpora become increasingly exhausted, clean long-context documents have become a scarce and expensive source of training data for large language models (LLMs).

By Nick Bettencourt, Xiaowei Ding, Kay Giesecke

llms computer-vision benchmarks

arXiv AI

Jun 24

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

arXiv:2606. 23032v2 Announce Type: replace Abstract: 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.

By Mostapha Benhenda

llms agents benchmarks safety

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

Jul 1

IPO Finance Agent: Benchmark of LLM Financial Analysts Beyond Finance Agent v2, with Automated Rubric Generation, on the SpaceX (SPCX) IPO

arXiv:2606. 23032v3 Announce Type: replace Abstract: 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.

By Mostapha Benhenda

llms agents benchmarks safety

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.

By Yidong Jiang, Junrong Chen, Eftychia Makri, Jialin Chen, Peiwen Li, Ali Maatouk, Leandros Tassiulas, Eliot Brenner, Bing Xiang, Rex Ying

llms rag benchmarks safety

arXiv AI

Aug 6

MIDAS: Multi-LLM Iterative Data-Adaptive Summarization

arXiv:2608. 04307v1 Announce Type: cross Abstract: Text summarization is deceptively difficult.

By Karen Lee, Dhanashree Balaram, Seojun Shon, Umair Rasheed

llms nlp benchmarks

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 Machine Learning

Jun 25

MacroLens: A Multi-Task Benchmark for Contextual Financial Reasoning under Macroeconomic Scenarios

arXiv:2606. 24950v1 Announce Type: new Abstract: Financial decision-making is contextual: forecasting prices, valuing companies, and assessing event exposure weigh price history, accounting fundamentals, macroeconomic regime, and contemporaneous text.

By Patara Trirat, Jin Myung Kwak, Jay Heo, Heejun Lee, Sung Ju Hwang

llms fine-tuning benchmarks

arXiv AI

Jun 2

HiFi-KPI: A Dataset for Hierarchical KPI Extraction from Earnings Filings

arXiv:2502. 15411v4 Announce Type: replace-cross Abstract: Accurate tagging of earnings reports can yield significant short-term returns for stakeholders.

By Rasmus Aavang, Giovanni Rizzi, Rasmus B{\o}ggild, Alexandre Iolov, Mike Zhang, Johannes Bjerva

llms

arXiv AI

Jul 24

Frontier Financial Judgement: Can agents tell what might move a stock?

arXiv:2607. 20645v1 Announce Type: cross Abstract: We introduce Frontier Financial Judgement, a challenging new benchmark developed in collaboration with professional equity analysts to assess agents' ability to replicate expert human judgements.

By Joshua Harris

llms agents benchmarks

arXiv Machine Learning

Jul 24

Naver-News-KO: A Korean News Summarization Dataset for Open-Source Fine-Tuning of Summarization Models

arXiv:2607. 20442v1 Announce Type: cross Abstract: We release Naver-News-KO, a Korean news summarization dataset of 27,400 (document, summary) pairs collected from Naver News over a ten-day window in July 2022 across two categories (Economy and IT/Science; 77/23 split), with train/validation/test partitions of 22,194 / 2,466 / 2,740 and a mean per-record document-to-summary character-compression ratio of 6.

By Daekeun Kim

nlp fine-tuning benchmarks

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