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Autonomous agents have long been a prominent research focus in both academic and industry communities. Previous research in this field often focuses on training agents with limited knowledge within isolated environments, which diverges…

Artificial Intelligence · Computer Science 2025-03-04 Lei Wang , Chen Ma , Xueyang Feng , Zeyu Zhang , Hao Yang , Jingsen Zhang , Zhiyuan Chen , Jiakai Tang , Xu Chen , Yankai Lin , Wayne Xin Zhao , Zhewei Wei , Ji-Rong Wen

The rise of large language models (LLMs) has led many researchers to consider their usage for scientific work. Some have found benefits using LLMs to augment or automate aspects of their research pipeline, while others have urged caution…

Computation and Language · Computer Science 2024-11-11 Zhehui Liao , Maria Antoniak , Inyoung Cheong , Evie Yu-Yen Cheng , Ai-Heng Lee , Kyle Lo , Joseph Chee Chang , Amy X. Zhang

Empowered by vast internal knowledge reservoir, the new generation of large language models (LLMs) demonstrate untapped potential to tackle medical tasks. However, there is insufficient effort made towards summoning up a synergic effect…

Computation and Language · Computer Science 2025-05-23 Kexin Shang , Chia-Hsuan Chang , Christopher C. Yang

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

As the applications of large language models (LLMs) expand across diverse fields, the ability of these models to adapt to ongoing changes in data, tasks, and user preferences becomes crucial. Traditional training methods, relying on static…

Machine Learning · Computer Science 2024-06-11 Junhao Zheng , Shengjie Qiu , Chengming Shi , Qianli Ma

In the past year, MultiModal Large Language Models (MM-LLMs) have undergone substantial advancements, augmenting off-the-shelf LLMs to support MM inputs or outputs via cost-effective training strategies. The resulting models not only…

Computation and Language · Computer Science 2024-05-29 Duzhen Zhang , Yahan Yu , Jiahua Dong , Chenxing Li , Dan Su , Chenhui Chu , Dong Yu

Language models serve as a cornerstone in natural language processing (NLP), utilizing mathematical methods to generalize language laws and knowledge for prediction and generation. Over extensive research spanning decades, language modeling…

Computation and Language · Computer Science 2024-09-24 Zichong Wang , Zhibo Chu , Thang Viet Doan , Shiwen Ni , Min Yang , Wenbin Zhang

Large language models (LLMs) are powerful artificial intelligence (AI) tools transforming how research is conducted. However, their use in research has been met with skepticism, due to concerns about hallucinations, biases and potential…

Artificial Intelligence · Computer Science 2025-07-08 Ruian Ke , Ruy M. Ribeiro

Large Language Models (LLMs) have demonstrated remarkable performance across various natural language tasks, marking significant strides towards general artificial intelligence. While general artificial intelligence is leveraged by…

Computation and Language · Computer Science 2023-10-31 Yizhe Yang , Huashan Sun , Jiawei Li , Runheng Liu , Yinghao Li , Yuhang Liu , Heyan Huang , Yang Gao

Multimodal Large Language Models (MLLMs) are gaining increasing popularity in both academia and industry due to their remarkable performance in various applications such as visual question answering, visual perception, understanding, and…

Computation and Language · Computer Science 2024-09-09 Jian Li , Weiheng Lu , Hao Fei , Meng Luo , Ming Dai , Min Xia , Yizhang Jin , Zhenye Gan , Ding Qi , Chaoyou Fu , Ying Tai , Wankou Yang , Yabiao Wang , Chengjie Wang

Topic modelling, as a well-established unsupervised technique, has found extensive use in automatically detecting significant topics within a corpus of documents. However, classic topic modelling approaches (e.g., LDA) have certain…

Computation and Language · Computer Science 2024-03-27 Yida Mu , Chun Dong , Kalina Bontcheva , Xingyi Song

The planning ability of Large Language Models (LLMs) has garnered increasing attention in recent years due to their remarkable capacity for multi-step reasoning and their ability to generalize across a wide range of domains. While some…

Artificial Intelligence · Computer Science 2025-02-19 Mohamed Aghzal , Erion Plaku , Gregory J. Stein , Ziyu Yao

Large Language Models (LLMs) have achieved remarkable success across a wide array of tasks. Due to the impressive planning and reasoning abilities of LLMs, they have been used as autonomous agents to do many tasks automatically. Recently,…

Computation and Language · Computer Science 2024-04-22 Taicheng Guo , Xiuying Chen , Yaqi Wang , Ruidi Chang , Shichao Pei , Nitesh V. Chawla , Olaf Wiest , Xiangliang Zhang

Large language models (LLMs) have demonstrated remarkable capabilities across various NLP tasks and have recently expanded their impact to coding tasks, bridging the gap between natural languages (NL) and programming languages (PL). This…

Computation and Language · Computer Science 2024-12-12 Nishat Raihan , Christian Newman , Marcos Zampieri

Large language models (LLMs) enable researchers to analyze text at unprecedented scale and minimal cost. Researchers can now revisit old questions and tackle novel ones with rich data. We provide an econometric framework for realizing this…

Econometrics · Economics 2025-12-08 Jens Ludwig , Sendhil Mullainathan , Ashesh Rambachan

Large language models (LLMs) are a class of artificial intelligence models based on deep learning, which have great performance in various tasks, especially in natural language processing (NLP). Large language models typically consist of…

Quantitative Methods · Quantitative Biology 2025-02-04 Jiajia Liu , Mengyuan Yang , Yankai Yu , Haixia Xu , Tiangang Wang , Kang Li , Xiaobo Zhou

Generative Pretrained Transformers (GPTs) are foundational Large Language Models (LLMs) for text generation. However, individual LLMs often produce inconsistent outputs and exhibit biases, limiting their representation of diverse language…

Computation and Language · Computer Science 2025-08-06 Mari Ashiga , Wei Jie , Fan Wu , Vardan Voskanyan , Fateme Dinmohammadi , Paul Brookes , Jingzhi Gong , Zheng Wang

Efficient processing of long contexts has been a persistent pursuit in Natural Language Processing. With the growing number of long documents, dialogues, and other textual data, it is important to develop Long Context Language Models…

The deployment of large language models (LLMs) within the healthcare sector has sparked both enthusiasm and apprehension. These models exhibit the remarkable capability to provide proficient responses to free-text queries, demonstrating a…

Computation and Language · Computer Science 2024-07-09 Zabir Al Nazi , Wei Peng

To facilitate the research on large language models (LLMs), this paper presents a comprehensive and unified library, LLMBox, to ease the development, use, and evaluation of LLMs. This library is featured with three main merits: (1) a…