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Pretrained large language models (LLMs) are currently state-of-the-art for solving the vast majority of natural language processing tasks. While many real-world applications still require fine-tuning to reach satisfactory levels of…

Despite representing nearly one-third of the world's languages, African languages remain critically underserved by modern NLP technologies, with 88\% classified as severely underrepresented or completely ignored in computational…

Large Language Models (LLMs), through their contextualized representations, have been empirically proven to encapsulate syntactic, semantic, word sense, and common-sense knowledge. However, there has been limited exploration of their…

Computation and Language · Computer Science 2023-10-12 Yi Ru Wang , Jiafei Duan , Dieter Fox , Siddhartha Srinivasa

Despite multilingual pretraining, large language models often struggle with non-English tasks, particularly in language control, the ability to respond in the intended language. We identify and characterize two key failure modes: the…

Computation and Language · Computer Science 2026-03-24 J. Ben Tamo , Daniel Carlander-Reuterfelt , Jonathan Rubin , Dezhi Hong , Mingxian Wang , Oleg Poliannikov

Tool learning, which enables large language models (LLMs) to utilize external tools effectively, has garnered increasing attention for its potential to revolutionize productivity across industries. Despite rapid development in tool…

Artificial Intelligence · Computer Science 2025-05-20 Haotian Chen , Zijun Song , Boye Niu , Ke Zhang , Litu Ou , Yaxi Lu , Zhong Zhang , Xin Cong , Yankai Lin , Zhiyuan Liu , Maosong Sun

Trained on the large corpus, pre-trained language models (PLMs) can capture different levels of concepts in context and hence generate universal language representations. They can benefit multiple downstream natural language processing…

Computation and Language · Computer Science 2021-10-15 Nankai Lin , Yingwen Fu , Chuwei Chen , Ziyu Yang , Shengyi Jiang

Multimodal language analysis is a rapidly evolving field that leverages multiple modalities to enhance the understanding of high-level semantics underlying human conversational utterances. Despite its significance, little research has…

Computation and Language · Computer Science 2025-04-25 Hanlei Zhang , Zhuohang Li , Yeshuang Zhu , Hua Xu , Peiwu Wang , Haige Zhu , Jie Zhou , Jinchao Zhang

Transformer is a state-of-the-art model in the field of natural language processing (NLP). Current NLP models primarily increase the number of transformers to improve processing performance. However, this technique requires a lot of…

Computation and Language · Computer Science 2023-10-18 Woohyeon Moon , Taeyoung Kim , Bumgeun Park , Dongsoo Har

Large language models (LLMs) can potentially democratize access to medical knowledge. While many efforts have been made to harness and improve LLMs' medical knowledge and reasoning capacities, the resulting models are either closed-source…

Large Language Models (LLMs), such as Generative Pre-trained Transformers (GPTs) are revolutionizing the generation of human-like text, producing contextually relevant and syntactically correct content. Despite challenges like biases and…

Computation and Language · Computer Science 2025-08-04 Alper Yaman , Jannik Schwab , Christof Nitsche , Abhirup Sinha , Marco Huber

Multilingual pretrained language models (mPLMs) acquire valuable, generalizable linguistic information during pretraining and have advanced the state of the art on task-specific finetuning. To date, only ~31 out of ~2,000 African languages…

Computation and Language · Computer Science 2023-05-30 Ife Adebara , AbdelRahim Elmadany , Muhammad Abdul-Mageed , Alcides Alcoba Inciarte

Large language models (LLM) such as OpenAI's ChatGPT and GPT-3 offer unique testbeds for exploring the translation challenges of turning literacy into numeracy. Previous publicly-available transformer models from eighteen months prior and…

Computation and Language · Computer Science 2023-02-01 David Noever , Forrest McKee

Multilingual language models have significantly advanced due to rapid progress in natural language processing. Models like BLOOM 1.7B, trained on diverse multilingual datasets, aim to bridge linguistic gaps. However, their effectiveness in…

Computation and Language · Computer Science 2026-02-03 Santhosh Kakarla , Gautama Shastry Bulusu Venkata , Aishwarya Gaddam , Maheedhar Sai Omtri Mohan

Large language models (LLMs) use pretraining to predict the subsequent word; however, their expansion requires significant computing resources. Numerous big tech companies and research institutes have developed multilingual LLMs (MLLMs) to…

The rapid evolution of Multimodal Large Language Models (MLLMs) has brought substantial advancements in artificial intelligence, significantly enhancing the capability to understand and generate multimodal content. While prior studies have…

Artificial Intelligence · Computer Science 2024-09-30 Lin Li , Guikun Chen , Hanrong Shi , Jun Xiao , Long Chen

Background: Clinical natural language processing (NLP) refers to the use of computational methods for extracting, processing, and analyzing unstructured clinical text data, and holds a huge potential to transform healthcare in various…

We introduce a dataset of high-quality human-authored summaries of news articles in Norwegian. The dataset is intended for benchmarking the abstractive summarisation capabilities of generative language models. Each document in the dataset…

Computation and Language · Computer Science 2025-01-15 Samia Touileb , Vladislav Mikhailov , Marie Kroka , Lilja Øvrelid , Erik Velldal

When learning a new skill, you take advantage of your preexisting skills and knowledge. For instance, if you are a skilled violinist, you will likely have an easier time learning to play cello. Similarly, when learning a new language you…

Computation and Language · Computer Science 2017-11-06 Johannes Bjerva

Large Language Models (LLMs) have made significant progress in reasoning, demonstrating their capability to generate human-like responses. This study analyzes the problem-solving capabilities of LLMs in the domain of thermodynamics. A…

Computational Engineering, Finance, and Science · Computer Science 2025-12-18 Rebecca Loubet , Pascal Zittlau , Luisa Vollmer , Marco Hoffmann , Sophie Fellenz , Fabian Jirasek , Heike Leitte , Hans Hasse

Recent advancements in large language models (LLMs) have revolutionized various domains, bringing significant progress and new opportunities. Despite progress in speech-related tasks, LLMs have not been sufficiently explored in multi-talker…

Computation and Language · Computer Science 2025-04-03 Lingwei Meng , Shujie Hu , Jiawen Kang , Zhaoqing Li , Yuejiao Wang , Wenxuan Wu , Xixin Wu , Xunying Liu , Helen Meng
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