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Large Language Models (LLMs) hold the potential to revolutionize autoformalization. The introduction of Lean4, a mathematical programming language, presents an unprecedented opportunity to rigorously assess the autoformalization…

机器学习 · 计算机科学 2024-06-12 Aryan Gulati , Devanshu Ladsaria , Shubhra Mishra , Jasdeep Sidhu , Brando Miranda

Large language models (LLMs), such as ChatGPT, have rapidly penetrated into people's work and daily lives over the past few years, due to their extraordinary conversational skills and intelligence. ChatGPT has become the fastest-growing…

计算与语言 · 计算机科学 2024-09-04 Wenxuan Wang

The integration of Large Language Models (LLMs) into financial analysis has garnered significant attention in the NLP community. This paper presents our solution to IJCAI-2024 FinLLM challenge, investigating the capabilities of LLMs within…

计算工程、金融与科学 · 计算机科学 2024-07-03 Yupeng Cao , Zhiyuan Yao , Zhi Chen , Zhiyang Deng

Recent advances in large language models (LLMs) have unlocked novel opportunities for machine learning applications in the financial domain. These models have demonstrated remarkable capabilities in understanding context, processing vast…

综合金融 · 定量金融 2024-06-19 Yuqi Nie , Yaxuan Kong , Xiaowen Dong , John M. Mulvey , H. Vincent Poor , Qingsong Wen , Stefan Zohren

Large language models (LLMs) are increasingly being used for complex research tasks such as literature review, idea generation, and scientific paper analysis, yet their ability to truly understand and process the intricate relationships…

计算与语言 · 计算机科学 2025-06-11 Shashidhar Reddy Javaji , Yupeng Cao , Haohang Li , Yangyang Yu , Nikhil Muralidhar , Zining Zhu

There is a significant gap between patient needs and available mental health support today. In this paper, we aim to thoroughly examine the potential of using Large Language Models (LLMs) to assist professional psychotherapy. To this end,…

While Large Language Models (LLMs) excel in various general domains, they exhibit notable gaps in the highly specialized, knowledge-intensive, and legally regulated Chinese tax domain. Consequently, while tax-related benchmarks are gaining…

计算与语言 · 计算机科学 2026-04-23 Gang Hu , Yating Chen , Haiyan Ding , Wang Gao , Jiajia Huang , Min Peng , Qianqian Xie , Kun Yue

Recent advancements in Large Language Models (LLMs), such as ChatGPT and LLaMA, have significantly transformed Natural Language Processing (NLP) with their outstanding abilities in text generation, summarization, and classification.…

计算与语言 · 计算机科学 2024-08-12 Md Nazmus Sakib , Md Athikul Islam , Royal Pathak , Md Mashrur Arifin

The growing complexity and diversity of news coverage have made framing analysis a crucial yet challenging task in computational social science. Traditional approaches, including manual annotation and fine-tuned models, remain limited by…

计算与语言 · 计算机科学 2026-05-22 Valeria Pastorino , Jasivan A. Sivakumar , Nafise Sadat Moosavi

Generative AI-powered by Large Language Models (LLMs)-is increasingly deployed in industry across healthcare decision support, financial analytics, enterprise retrieval, and conversational automation, where reliability, efficiency, and cost…

Artificial Intelligence (AI) is taking on increasingly autonomous roles, e.g., browsing the web as a research assistant and managing money. But specifying goals and restrictions for AI behavior is difficult. Similar to how parties to a…

计算与语言 · 计算机科学 2023-01-31 John J. Nay

Large Language Models (LLMs) have garnered considerable interest within both academic and industrial. Yet, the application of LLMs to graph data remains under-explored. In this study, we evaluate the capabilities of four LLMs in addressing…

人工智能 · 计算机科学 2023-09-12 Chang Liu , Bo Wu

Large language models (LLMs) have exhibited an array of reasoning capabilities but face challenges like error propagation and hallucination, particularly in specialised areas like finance, where data is heterogeneous, and precision is…

计算与语言 · 计算机科学 2024-01-31 Adrian Theuma , Ehsan Shareghi

Large Language Models (LLMs) like ChatGPT and GPT-4 have demonstrated impressive proficiency in comprehending and generating natural language. However, they encounter difficulties when tasked with adapting to specialized domains such as…

计算与语言 · 计算机科学 2024-02-27 Jiayuan Luo , Songhua Yang , Xiaoling Qiu , Panyu Chen , Yufei Nai , Wenxuan Zeng , Wentao Zhang , Xinke Jiang

While large language models (LLMs) have demonstrated impressive capabilities across various natural language processing tasks by acquiring rich factual knowledge from their broad training data, their ability to synthesize and logically…

计算与语言 · 计算机科学 2024-07-31 Tianshi Zheng , Jiaxin Bai , Yicheng Wang , Tianqing Fang , Yue Guo , Yauwai Yim , Yangqiu Song

The rapid evolution of Large Language Models (LLMs) presents a promising solution to the global shortage of mental health professionals. However, their alignment with essential counseling competencies remains underexplored. We introduce…

Large Language Models (LLMs), such as ChatGPT, LLaMA, GLM, and PaLM, have exhibited remarkable performances across various tasks in recent years. However, LLMs face two main challenges in real-world applications. One challenge is that…

机器学习 · 计算机科学 2023-10-17 Tao Fan , Yan Kang , Guoqiang Ma , Weijing Chen , Wenbin Wei , Lixin Fan , Qiang Yang

The rapid advancements in Large Language Models (LLMs) have unlocked transformative possibilities in natural language processing, particularly within the financial sector. Financial data is often embedded in intricate relationships across…

统计金融 · 定量金融 2026-05-21 Alejandro Lopez-Lira , Jihoon Kwon , Sangwoon Yoon , Jy-yong Sohn , Chanyeol Choi

Large language models (LLMs) are increasingly being applied to financial analysis, reporting, investment decision support, risk management, compliance, and professional training. However, robust evaluation of their domain competence in…

Large language models (LLMs) have demonstrated remarkable capabilities across a wide range of tasks in various domains. Despite their impressive performance, they can be unreliable due to factual errors in their generations. Assessing their…

计算与语言 · 计算机科学 2024-03-26 Jiahui Geng , Fengyu Cai , Yuxia Wang , Heinz Koeppl , Preslav Nakov , Iryna Gurevych