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Large language models (LLMs) are competitive with the state of the art on a wide range of sentence-level translation datasets. However, their ability to translate paragraphs and documents remains unexplored because evaluation in these…

Computation and Language · Computer Science 2023-05-24 Marzena Karpinska , Mohit Iyyer

The rapid advancement of Multimodal Large Language Models (MLLMs) has been accompanied by the development of various benchmarks to evaluate their capabilities. However, the true nature of these evaluations and the extent to which they…

Computation and Language · Computer Science 2024-10-17 Botian Jiang , Lei Li , Xiaonan Li , Zhaowei Li , Xiachong Feng , Lingpeng Kong , Qi Liu , Xipeng Qiu

We introduce a new benchmark for assessing the quality of text-to-text models for Polish. The benchmark consists of diverse tasks and datasets: KLEJ benchmark adapted for text-to-text, en-pl translation, summarization, and question…

Computation and Language · Computer Science 2022-05-19 Aleksandra Chrabrowa , Łukasz Dragan , Karol Grzegorczyk , Dariusz Kajtoch , Mikołaj Koszowski , Robert Mroczkowski , Piotr Rybak

To ensure equitable access to the benefits of large language models (LLMs), it is essential to evaluate their capabilities across the world's languages. We introduce the AI Language Proficiency Monitor, a comprehensive multilingual…

Computation and Language · Computer Science 2025-07-14 David Pomerenke , Jonas Nothnagel , Simon Ostermann

Large Language Models (LLMs) with strong abilities in natural language processing tasks have emerged and have been applied in various kinds of areas such as science, finance and software engineering. However, the capability of LLMs to…

Computation and Language · Computer Science 2023-12-29 Taicheng Guo , Kehan Guo , Bozhao Nan , Zhenwen Liang , Zhichun Guo , Nitesh V. Chawla , Olaf Wiest , Xiangliang Zhang

The widespread adoption and increasing prominence of large language models (LLMs) in global technologies necessitate a rigorous focus on ensuring their safety across a diverse range of linguistic and cultural contexts. The lack of a…

Computation and Language · Computer Science 2025-08-28 Zhiyuan Ning , Tianle Gu , Jiaxin Song , Shixin Hong , Lingyu Li , Huacan Liu , Jie Li , Yixu Wang , Meng Lingyu , Yan Teng , Yingchun Wang

In some areas of computing, natural language processing and information science, progress is made by sharing datasets and challenging the community to design the best algorithm for an associated task. This article introduces a shared…

Digital Libraries · Computer Science 2026-01-27 Mike Thelwall

Ensuring the general efficacy and goodness for human beings from medical large language models (LLM) before real-world deployment is crucial. However, a widely accepted and accessible evaluation process for medical LLM, especially in the…

Large Language Models (LLMs) have demonstrated their transformative potential across numerous disciplinary studies, reshaping the existing research methodologies and fostering interdisciplinary collaboration. However, a systematic…

Computation and Language · Computer Science 2025-07-14 Lu Xiang , Yang Zhao , Yaping Zhang , Chengqing Zong

Large language models (LLMs) are transforming the ways the general public accesses and consumes information. Their influence is particularly pronounced in pivotal sectors like healthcare, where lay individuals are increasingly appropriating…

Computation and Language · Computer Science 2023-10-24 Yiqiao Jin , Mohit Chandra , Gaurav Verma , Yibo Hu , Munmun De Choudhury , Srijan Kumar

The advent of large language models (LLMs) and their adoption by the legal community has given rise to the question: what types of legal reasoning can LLMs perform? To enable greater study of this question, we present LegalBench: a…

Large Language Models (LLMs) have the potential to semi-automate some process mining (PM) analyses. While commercial models are already adequate for many analytics tasks, the competitive level of open-source LLMs in PM tasks is unknown. In…

Computation and Language · Computer Science 2024-07-19 Alessandro Berti , Humam Kourani , Wil M. P. van der Aalst

Large Language Models (LLMs) play a critical role in how humans access information. While their core use relies on comprehending written requests, our understanding of this ability is currently limited, because most benchmarks evaluate LLMs…

We introduce ChemPro, a progressive benchmark with 4100 natural language question-answer pairs in Chemistry, across 4 coherent sections of difficulty designed to assess the proficiency of Large Language Models (LLMs) in a broad spectrum of…

Computation and Language · Computer Science 2026-04-22 Aaditya Baranwal , Shruti Vyas

Large Language Models (LLMs) have demonstrated remarkable instruction-following capabilities across various applications. However, their performance in multilingual settings lacks systematic investigation, with existing evaluations lacking…

Computation and Language · Computer Science 2025-11-04 Zhenyu Li , Kehai Chen , Yunfei Long , Xuefeng Bai , Yaoyin Zhang , Xuchen Wei , Juntao Li , Min Zhang

Large Language Models (LLMs) are increasingly explored for educational tasks such as grading, yet their alignment with human evaluation in real classrooms remains underexamined. In this study, we investigate the feasibility of using an LLM…

Computation and Language · Computer Science 2025-11-19 Grace Byun , Swati Rajwal , Jinho D. Choi

As the importance of comprehensive evaluation in workshop courses increases, there is a growing demand for efficient and fair assessment methods that reduce the workload for faculty members. This paper presents an evaluation conducted with…

Computers and Society · Computer Science 2024-05-30 Toru Ishida , Tongxi Liu , Hailong Wang , William K. Cheung

For multilingual factual knowledge assessment of LLMs, benchmarks such as MLAMA use template translations that do not take into account the grammatical and semantic information of the named entities inserted in the sentence. This leads to…

Computation and Language · Computer Science 2025-10-20 Kirill Semenov , Rico Sennrich

Recent advancements in Large Language Models (LLMs) have markedly enhanced the interpretation and processing of tabular data, introducing previously unimaginable capabilities. Despite these achievements, LLMs still encounter significant…

Computation and Language · Computer Science 2025-03-19 Xianjie Wu , Jian Yang , Linzheng Chai , Ge Zhang , Jiaheng Liu , Xinrun Du , Di Liang , Daixin Shu , Xianfu Cheng , Tianzhen Sun , Guanglin Niu , Tongliang Li , Zhoujun Li