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Large language models (LLMs) are increasingly being adopted in educational settings. These applications expand beyond English, though current LLMs remain primarily English-centric. In this work, we ascertain if their use in education…

Computation and Language · Computer Science 2025-08-06 Vansh Gupta , Sankalan Pal Chowdhury , Vilém Zouhar , Donya Rooein , Mrinmaya Sachan

With the rising human-like precision of Large Language Models (LLMs) in numerous tasks, their utilization in a variety of real-world applications is becoming more prevalent. Several studies have shown that LLMs excel on many standard NLP…

Computation and Language · Computer Science 2024-04-03 Rishav Hada , Varun Gumma , Mohamed Ahmed , Kalika Bali , Sunayana Sitaram

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…

Machine Learning · Computer Science 2023-10-17 Tao Fan , Yan Kang , Guoqiang Ma , Weijing Chen , Wenbin Wei , Lixin Fan , Qiang Yang

Business Process Management (BPM) aims to improve organizational activities and their outcomes by managing the underlying processes. To achieve this, it is often necessary to consider information from various sources, including unstructured…

Computation and Language · Computer Science 2023-07-20 Michael Grohs , Luka Abb , Nourhan Elsayed , Jana-Rebecca Rehse

The rise of Large Language Models (LLMs) has revolutionized natural language processing across numerous languages and tasks. However, evaluating LLM performance in a consistent and meaningful way across multiple European languages remains…

Large language models (LLMs), a recent advance in deep learning and machine intelligence, have manifested astonishing capacities, now considered among the most promising for artificial general intelligence. With human-like capabilities,…

Artificial Intelligence · Computer Science 2025-09-19 Zhilun Zhou , Jing Yi Wang , Nicholas Sukiennik , Chen Gao , Fengli Xu , Yong Li , James Evans

Large language models (LLMs) have become powerful tools for advancing natural language processing applications in the financial industry. However, existing financial LLMs often face challenges such as hallucinations or superficial parameter…

Computation and Language · Computer Science 2024-08-06 Shujuan Zhao , Lingfeng Qiao , Kangyang Luo , Qian-Wen Zhang , Junru Lu , Di Yin

While pre-trained language models (LMs) have brought great improvements in many NLP tasks, there is increasing attention to explore capabilities of LMs and interpret their predictions. However, existing works usually focus only on a certain…

Computation and Language · Computer Science 2022-07-29 Yaozong Shen , Lijie Wang , Ying Chen , Xinyan Xiao , Jing Liu , Hua Wu

Large Language Models (LLMs) are increasingly employed for simulating human behaviors across diverse domains. However, our position is that current LLM-based human simulations remain insufficiently reliable, as evidenced by significant…

Computation and Language · Computer Science 2025-12-02 Qian Wang , Jiaying Wu , Zichen Jiang , Zhenheng Tang , Bingqiao Luo , Nuo Chen , Wei Chen , Bingsheng He

While Large Language Models (LLMs) can accelerate text-heavy tasks in alternative investment due diligence, a gap remains in their ability to accurately extract and reason over structured tabular data from complex financial spreadsheets.…

Artificial Intelligence · Computer Science 2026-03-10 Jan Ravnik , Matjaž Ličen , Felix Bührmann , Bithiah Yuan , Felix Stinson , Tanvi Singh

LLMs have gotten attention across various research domains due to their exceptional performance on a wide range of complex tasks. Therefore, refined methods to evaluate the capabilities of LLMs are needed to determine the tasks and…

Computation and Language · Computer Science 2024-06-04 Ji-Lun Peng , Sijia Cheng , Egil Diau , Yung-Yu Shih , Po-Heng Chen , Yen-Ting Lin , Yun-Nung Chen

Large language models (LLMs) have demonstrated remarkable performance on various medical benchmarks, but their capabilities across different cognitive levels remain underexplored. Inspired by Bloom's Taxonomy, we propose a…

Computation and Language · Computer Science 2025-06-11 Yuxuan Zhou , Xien Liu , Chenwei Yan , Chen Ning , Xiao Zhang , Boxun Li , Xiangling Fu , Shijin Wang , Guoping Hu , Yu Wang , Ji Wu

Despite impressive results on curated benchmarks, the practical impact of large language models (LLMs) on research-level neural theorem proving and proof autoformalization is still limited. We introduce RLMEval, an evaluation suite for…

Computation and Language · Computer Science 2025-10-30 Auguste Poiroux , Antoine Bosselut , Viktor Kunčak

Large language models (LLMs) achieve astonishing results on a wide range of tasks. However, their formal reasoning ability still lags behind. A promising approach is Neurosymbolic LLM reasoning. It works by using LLMs as translators from…

Artificial Intelligence · Computer Science 2025-09-05 Alexander Beiser , David Penz , Nysret Musliu

This paper presents a comprehensive evaluation of cost-efficient Large Language Models (LLMs) for diverse biomedical tasks spanning both text and image modalities. We evaluated a range of closed-source and open-source LLMs on tasks such as…

Computation and Language · Computer Science 2025-07-21 Israt Jahan , Md Tahmid Rahman Laskar , Chun Peng , Jimmy Huang

Large language models (LLMs) have shown the potential of revolutionizing natural language processing tasks in diverse domains, sparking great interest in finance. Accessing high-quality financial data is the first challenge for financial…

Statistical Finance · Quantitative Finance 2025-11-18 Hongyang Yang , Xiao-Yang Liu , Christina Dan Wang

Large language models (LLMs) are gaining increasing popularity in both academia and industry, owing to their unprecedented performance in various applications. As LLMs continue to play a vital role in both research and daily use, their…

Computation and Language · Computer Science 2024-01-01 Yupeng Chang , Xu Wang , Jindong Wang , Yuan Wu , Linyi Yang , Kaijie Zhu , Hao Chen , Xiaoyuan Yi , Cunxiang Wang , Yidong Wang , Wei Ye , Yue Zhang , Yi Chang , Philip S. Yu , Qiang Yang , Xing Xie

LLMs have demonstrated great capabilities in various NLP tasks. Different entities can further improve the performance of those LLMs on their specific downstream tasks by fine-tuning LLMs. When several entities have similar interested…

Machine Learning · Computer Science 2023-09-04 Weirui Kuang , Bingchen Qian , Zitao Li , Daoyuan Chen , Dawei Gao , Xuchen Pan , Yuexiang Xie , Yaliang Li , Bolin Ding , Jingren Zhou

Large Language Models (LLMs) show significant potential in economic and strategic interactions, where communication via natural language is often prevalent. This raises key questions: Do LLMs behave rationally? How do they perform compared…

Computation and Language · Computer Science 2026-03-03 Eilam Shapira , Omer Madmon , Itamar Reinman , Samuel Joseph Amouyal , Roi Reichart , Moshe Tennenholtz
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