Datasets for large language models: A comprehensive survey

Y Liu, J Cao, C Liu, K Ding, L ** - arxiv preprint arxiv:2402.18041, 2024‏ - arxiv.org
This paper embarks on an exploration into the Large Language Model (LLM) datasets,
which play a crucial role in the remarkable advancements of LLMs. The datasets serve as …

A survey of large language models for financial applications: Progress, prospects and challenges

Y Nie, Y Kong, X Dong, JM Mulvey, HV Poor… - arxiv preprint arxiv …, 2024‏ - arxiv.org
Recent advances in large language models (LLMs) have unlocked novel opportunities for
machine learning applications in the financial domain. These models have demonstrated …

Fincon: A synthesized llm multi-agent system with conceptual verbal reinforcement for enhanced financial decision making

Y Yu, Z Yao, H Li, Z Deng, Y Jiang… - Advances in …, 2025‏ - proceedings.neurips.cc
Large language models (LLMs) have demonstrated notable potential in conducting complex
tasks and are increasingly utilized in various financial applications. However, high-quality …

A survey on large language models for critical societal domains: Finance, healthcare, and law

ZZ Chen, J Ma, X Zhang, N Hao, A Yan… - arxiv preprint arxiv …, 2024‏ - arxiv.org
In the fast-evolving domain of artificial intelligence, large language models (LLMs) such as
GPT-3 and GPT-4 are revolutionizing the landscapes of finance, healthcare, and law …

Open-finllms: Open multimodal large language models for financial applications

Q **e, D Li, M **ao, Z Jiang, R **ang, X Zhang… - arxiv preprint arxiv …, 2024‏ - arxiv.org
Large language models (LLMs) have advanced financial applications, yet they often lack
sufficient financial knowledge and struggle with tasks involving multi-modal inputs like tables …

Xbrl agent: Leveraging large language models for financial report analysis

S Han, H Kang, B **, XY Liu, SY Yang - Proceedings of the 5th ACM …, 2024‏ - dl.acm.org
eXtensible Business Reporting Language (XBRL) has attained the status of the global de
facto standard for business reporting. However, its complexity poses significant barriers to …

DocMath-eval: Evaluating math reasoning capabilities of LLMs in understanding long and specialized documents

Y Zhao, Y Long, H Liu, R Kamoi, L Nan, L Chen… - arxiv preprint arxiv …, 2023‏ - arxiv.org
Recent LLMs have demonstrated remarkable performance in solving exam-like math word
problems. However, the degree to which these numerical reasoning skills are effective in …

No language is an island: Unifying chinese and english in financial large language models, instruction data, and benchmarks

G Hu, K Qin, C Yuan, M Peng, A Lopez-Lira… - arxiv preprint arxiv …, 2024‏ - arxiv.org
While the progression of Large Language Models (LLMs) has notably propelled financial
analysis, their application has largely been confined to singular language realms, leaving …

Peer review as a multi-turn and long-context dialogue with role-based interactions

C Tan, D Lyu, S Li, Z Gao, J Wei, S Ma, Z Liu… - arxiv preprint arxiv …, 2024‏ - arxiv.org
Large Language Models (LLMs) have demonstrated wide-ranging applications across
various fields and have shown significant potential in the academic peer-review process …

Financemath: Knowledge-intensive math reasoning in finance domains

Y Zhao, H Liu, Y Long, R Zhang, C Zhao… - arxiv preprint arxiv …, 2023‏ - arxiv.org
We introduce FinanceMath, a novel benchmark designed to evaluate LLMs' capabilities in
solving knowledge-intensive math reasoning problems. Compared to prior works, this study …