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In the rapidly evolving landscape of artificial intelligence, multi-modal large language models are emerging as a significant area of interest. These models, which combine various forms of data input, are becoming increasingly popular.…

As large language models become increasingly capable, there is growing concern that they may develop reasoning processes that are encoded or hidden from human oversight. To investigate whether current interpretability techniques can…

Artificial Intelligence · Computer Science 2025-12-09 Ching Fang , Samuel Marks

The evolution of Large Language Models (LLMs) has showcased remarkable capacities for logical reasoning and natural language comprehension. These capabilities can be leveraged in solutions that semantically and textually model complex…

Human-Computer Interaction · Computer Science 2024-04-17 Syed Mekael Wasti , Ken Q. Pu , Ali Neshati

Understanding the internal representations of large language models (LLMs) can help explain models' behavior and verify their alignment with human values. Given the capabilities of LLMs in generating human-understandable text, we propose…

Computation and Language · Computer Science 2024-06-10 Asma Ghandeharioun , Avi Caciularu , Adam Pearce , Lucas Dixon , Mor Geva

Large language models (LLMs) have advanced the state of the art in natural language processing. However, their predominant design for English or a limited set of languages creates a substantial gap in their effectiveness for low-resource…

Computation and Language · Computer Science 2024-04-04 Peiqin Lin , Shaoxiong Ji , Jörg Tiedemann , André F. T. Martins , Hinrich Schütze

With the broader adoption and highly successful development of Large Language Models (LLMs), there has been growing interest and demand for applying LLMs to autonomous driving technology. Driven by their natural language understanding and…

Recent years have seen important advances in the building of interpretable models, machine learning models that are designed to be easily understood by humans. In this work, we show that large language models (LLMs) are remarkably good at…

Machine Learning · Computer Science 2024-02-23 Sebastian Bordt , Ben Lengerich , Harsha Nori , Rich Caruana

Large language models (LLMs) have made significant progress in various domains, including healthcare. However, the specialized nature of clinical language understanding tasks presents unique challenges and limitations that warrant further…

Computation and Language · Computer Science 2023-08-01 Yuqing Wang , Yun Zhao , Linda Petzold

Large language models (LLMs) and transformer-based architectures are increasingly utilized for source code analysis. As software systems grow in complexity, integrating LLMs into code analysis workflows becomes essential for enhancing…

Software Engineering · Computer Science 2025-03-25 Hamed Jelodar , Mohammad Meymani , Roozbeh Razavi-Far

Large language models (LLMs) have recently demonstrated their potential in clinical applications, providing valuable medical knowledge and advice. For example, a large dialog LLM like ChatGPT has successfully passed part of the US medical…

Computer Vision and Pattern Recognition · Computer Science 2023-02-15 Sheng Wang , Zihao Zhao , Xi Ouyang , Qian Wang , Dinggang Shen

Large Language Models (LLMs) have seen rapid advancements in recent years, with models like ChatGPT and DeepSeek, showcasing their remarkable capabilities across diverse domains. While substantial research has been conducted on LLMs in…

Machine Learning · Computer Science 2026-03-31 Licheng Zhang , Bach Le , Naveed Akhtar , Siew-Kei Lam , Tuan Ngo

The advent of Large Language Models (LLMs) has revolutionized language understanding and human-like text generation, drawing interest from many other fields with this question in mind: What else are the LLMs capable of? Despite their…

Artificial Intelligence · Computer Science 2024-10-24 Nurullah Sevim , Mostafa Ibrahim , Sabit Ekin

Multimodal large language models (MLLMs) have shown remarkable performance in vision-language tasks. However, existing MLLMs are primarily trained on generic datasets, limiting their ability to reason on domain-specific visual cues such as…

Computer Vision and Pattern Recognition · Computer Science 2025-07-15 Hatef Otroshi Shahreza , Sébastien Marcel

We aim to present a comprehensive overview of the latest advancements in utilizing Large Language Models (LLMs) within the healthcare sector, emphasizing their transformative impact across various medical domains. LLMs have become pivotal…

Computation and Language · Computer Science 2026-04-07 Ummara Mumtaz , Awais Ahmed , Summaya Mumtaz

The emergence of Multimodal Large Language Models (MLLMs) has revolutionized image understanding by bridging textual and visual modalities. However, these models often struggle with capturing fine-grained semantic information, such as the…

Computer Vision and Pattern Recognition · Computer Science 2025-07-16 Jie Yang , Wang Zeng , Sheng Jin , Lumin Xu , Wentao Liu , Chen Qian , Zhen Li , Ruimao Zhang

Large Language Models (LLMs) are transforming artificial intelligence, enabling autonomous agents to perform diverse tasks across various domains. These agents, proficient in human-like text comprehension and generation, have the potential…

Artificial Intelligence · Computer Science 2024-04-10 Saikat Barua

Recent advancements in large language models (LLMs) are propelling us toward artificial general intelligence with their remarkable emergent abilities and reasoning capabilities. However, the substantial computational and memory requirements…

Machine Learning · Computer Science 2024-10-10 Ruihao Gong , Yang Yong , Shiqiao Gu , Yushi Huang , Chengtao Lv , Yunchen Zhang , Xianglong Liu , Dacheng Tao

Recently, large language models (LLMs) have achieved remarkable breakthroughs in general domains such as programming and writing, and have demonstrated strong potential in various scientific research scenarios. However, the capabilities of…

Machine Learning · Computer Science 2025-09-16 Yonghao Weng , Liqiang Gao , Linwu Zhu , Jian Huang

Large Language Models (LLMs) have emerged as dominant foundational models in modern NLP. However, the understanding of their prediction processes and internal mechanisms, such as feed-forward networks (FFN) and multi-head self-attention…

Computation and Language · Computer Science 2024-04-16 Xintong Wang , Xiaoyu Li , Xingshan Li , Chris Biemann
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