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Large language models (LLMs) have rapidly evolved from general-purpose systems to multimodal models capable of processing text, images, and audio. As both general-purpose LLMs (GLLMs) and multimodal LLMs (MLLMs) gain widespread adoption,…

Software Engineering · Computer Science 2026-04-08 Yujian Liu , Xiao Yu , Jacky Keung , Xing Hu , Xin Xia , Xiaoxue Ma

We introduce ChatGLM, an evolving family of large language models that we have been developing over time. This report primarily focuses on the GLM-4 language series, which includes GLM-4, GLM-4-Air, and GLM-4-9B. They represent our most…

The success of large language models (LLMs) has inspired an emerging research field of multimodal learning. However, a grand challenge of exploiting LLMs for multimodal learning is the size of pre-trained LLMs which are always with billions…

Computation and Language · Computer Science 2024-04-08 Zhengqing Yuan , Yunhong He , Kun Wang , Yanfang Ye , Lichao Sun

Large language models (LLMs) have become central to modern AI workflows, powering applications from open-ended text generation to complex agent-based reasoning. However, debugging these models remains a persistent challenge due to their…

Empathetic dialogue is an indispensable part of building harmonious social relationships and contributes to the development of a helpful AI. Previous approaches are mainly based on fine small-scale language models. With the advent of…

Computation and Language · Computer Science 2024-07-29 Yushan Qian , Wei-Nan Zhang , Ting Liu

To address challenges in the digital economy's landscape of digital intelligence, large language models (LLMs) have been developed. Improvements in computational power and available resources have significantly advanced LLMs, allowing their…

Computation and Language · Computer Science 2024-05-24 Yanxin Zheng , Wensheng Gan , Zefeng Chen , Zhenlian Qi , Qian Liang , Philip S. Yu

One of the limitations of large language models is that they do not have access to up-to-date, proprietary or personal data. As a result, there are multiple efforts to extend language models with techniques for accessing external data. In…

Computation and Language · Computer Science 2023-04-11 Alon Halevy , Jane Dwivedi-Yu

The proliferation of large language models (LLMs) has revolutionized the capabilities of natural language interfaces (NLIs) for data analysis. LLMs can perform multi-step and complex reasoning to generate data insights based on users'…

Human-Computer Interaction · Computer Science 2024-12-24 Luoxuan Weng , Xingbo Wang , Junyu Lu , Yingchaojie Feng , Yihan Liu , Haozhe Feng , Danqing Huang , Wei Chen

Large Language Models (LLMs), typified by OpenAI's GPT, have marked a significant advancement in artificial intelligence. Trained on vast amounts of text data, LLMs are capable of understanding and generating human-like text across a…

Artificial Intelligence · Computer Science 2024-10-29 Haochen Zhang , Yuyang Dong , Chuan Xiao , Masafumi Oyamada

Recent research has highlighted the potential of large language models (LLMs) to improve their problem-solving capabilities with the aid of suitable external tools. In our work, we further advance this concept by introducing a closed-loop…

Machine Learning · Computer Science 2024-03-12 Tianle Cai , Xuezhi Wang , Tengyu Ma , Xinyun Chen , Denny Zhou

Artificial intelligence is making spectacular progress, and one of the best examples is the development of large language models (LLMs) such as OpenAI's GPT series. In these lectures, written for readers with a background in mathematics or…

Computation and Language · Computer Science 2023-10-09 Michael R. Douglas

Augmenting large language models (LLMs) with external tools has emerged as a promising approach to extend their utility, enabling them to solve practical tasks. Previous methods manually parse tool documentation and create in-context…

Computation and Language · Computer Science 2025-03-05 Zhengliang Shi , Shen Gao , Lingyong Yan , Yue Feng , Xiuyi Chen , Zhumin Chen , Dawei Yin , Suzan Verberne , Zhaochun Ren

This paper investigates the utilization of Large Language Models (LLMs) for solving complex linguistic puzzles, a domain requiring advanced reasoning and adept translation capabilities akin to human cognitive processes. We explore specific…

Computation and Language · Computer Science 2025-02-04 Zheng-Lin Lin , Yu-Fei Shih , Shu-Kai Hsieh

Multimodal Large Language Models (MLLMs) have achieved significant advances in integrating visual and linguistic information, yet their ability to reason about complex and real-world scenarios remains limited. The existing benchmarks are…

The disruptive technology provided by large-scale pre-trained language models (LLMs) such as ChatGPT or GPT-4 has received significant attention in several application domains, often with an emphasis on high-level opportunities and…

Human-Computer Interaction · Computer Science 2023-06-27 Philippe J. Giabbanelli

Logical reasoning is a fundamental aspect of human intelligence and a key component of tasks like problem-solving and decision-making. Recent advancements have enabled Large Language Models (LLMs) to potentially exhibit reasoning…

Computation and Language · Computer Science 2023-11-13 Jiazhan Feng , Ruochen Xu , Junheng Hao , Hiteshi Sharma , Yelong Shen , Dongyan Zhao , Weizhu Chen

Recently, tool learning with large language models (LLMs) has emerged as a promising paradigm for augmenting the capabilities of LLMs to tackle highly complex problems. Despite growing attention and rapid advancements in this field, the…

Computation and Language · Computer Science 2024-11-05 Changle Qu , Sunhao Dai , Xiaochi Wei , Hengyi Cai , Shuaiqiang Wang , Dawei Yin , Jun Xu , Ji-Rong Wen

The success of large language models (LLMs) has fostered a new research trend of multi-modality large language models (MLLMs), which changes the paradigm of various fields in computer vision. Though MLLMs have shown promising results in…

Computer Vision and Pattern Recognition · Computer Science 2024-06-12 Boyang Zheng , Jinjin Gu , Shijun Li , Chao Dong

The increasing complexity of software systems has driven significant advancements in program analysis, as traditional methods unable to meet the demands of modern software development. To address these limitations, deep learning techniques,…

Software Engineering · Computer Science 2025-02-27 Jiayimei Wang , Tao Ni , Wei-Bin Lee , Qingchuan Zhao

Large Language Models (LLMs) have been employed in financial decision making, enhancing analytical capabilities for investment strategies. Traditional investment strategies often utilize quantitative models, fundamental analysis, and…

General Finance · Quantitative Finance 2025-07-04 Sedigheh Mahdavi , Jiating , Chen , Pradeep Kumar Joshi , Lina Huertas Guativa , Upmanyu Singh