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In recent years, the integration of large language models (LLMs) has revolutionized the field of robotics, enabling robots to communicate, understand, and reason with human-like proficiency. This paper explores the multifaceted impact of…

Robotics · Computer Science 2024-08-16 Yeseung Kim , Dohyun Kim , Jieun Choi , Jisang Park , Nayoung Oh , Daehyung Park

There have been rapid advancements in the capabilities of large language models (LLMs) in recent years, greatly revolutionizing the field of natural language processing (NLP) and artificial intelligence (AI) to understand and interact with…

Computation and Language · Computer Science 2024-09-26 Zeyneb N. Kaya , Souvick Ghosh

Multimodal Large Language Models (MLLMs) have become increasingly important due to their state-of-the-art performance and ability to integrate multiple data modalities, such as text, images, and audio, to perform complex tasks with high…

Recent breakthroughs in large language modeling have facilitated rigorous exploration of their application in diverse tasks related to tabular data modeling, such as prediction, tabular data synthesis, question answering, and table…

Exploring the capabilities of Large Language Models (LLMs) in puzzle solving unveils critical insights into their potential and challenges in AI, marking a significant step towards understanding their applicability in complex reasoning…

Computation and Language · Computer Science 2025-08-04 Panagiotis Giadikiaroglou , Maria Lymperaiou , Giorgos Filandrianos , Giorgos Stamou

With the advancement of Artificial Intelligence (AI) and Large Language Models (LLMs), there is a profound transformation occurring in the realm of natural language processing tasks within the legal domain. The capabilities of LLMs are…

Computation and Language · Computer Science 2024-04-02 Weicong Qin , Zhongxiang Sun

Large language models (LLMs) have transformed many fields, including natural language processing, computer vision, and reinforcement learning. These models have also made a significant impact in the field of law, where they are being…

Computation and Language · Computer Science 2023-03-17 Zhongxiang Sun

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

Log data provides crucial insights for tasks like monitoring, root cause analysis, and anomaly detection. Due to the vast volume of logs, automated log parsing is essential to transform semi-structured log messages into structured…

Machine Learning · Computer Science 2025-05-16 Viktor Beck , Max Landauer , Markus Wurzenberger , Florian Skopik , Andreas Rauber

Large Language Models (LLMs) possess substantial reasoning capabilities and are increasingly applied to optimization tasks, particularly in synergy with evolutionary computation. However, while recent surveys have explored specific aspects…

Neural and Evolutionary Computing · Computer Science 2026-01-08 Yisong Zhang , Ran Cheng , Guoxing Yi , Kay Chen Tan

In the rapidly evolving domain of Natural Language Generation (NLG) evaluation, introducing Large Language Models (LLMs) has opened new avenues for assessing generated content quality, e.g., coherence, creativity, and context relevance.…

Computation and Language · Computer Science 2024-06-13 Zhen Li , Xiaohan Xu , Tao Shen , Can Xu , Jia-Chen Gu , Yuxuan Lai , Chongyang Tao , Shuai Ma

Large Language Models (LLMs) have emerged as a transformative power in enhancing natural language comprehension, representing a significant stride toward artificial general intelligence. The application of LLMs extends beyond conventional…

With the extensive application of Graph Neural Networks (GNNs) across various domains, their trustworthiness has emerged as a focal point of research. Some existing studies have shown that the integration of large language models (LLMs) can…

Machine Learning · Computer Science 2025-02-13 Ruizhan Xue , Huimin Deng , Fang He , Maojun Wang , Zeyu Zhang

Automatically annotating job data with standardized occupations from taxonomies, known as occupation classification, is crucial for labor market analysis. However, this task is often hindered by data scarcity and the challenges of manual…

Computation and Language · Computer Science 2025-11-03 Palakorn Achananuparp , Ee-Peng Lim , Yao Lu

This paper provides a comprehensive survey of the latest research on multilingual large language models (MLLMs). MLLMs not only are able to understand and generate language across linguistic boundaries, but also represent an important…

Computation and Language · Computer Science 2024-11-20 Shaolin Zhu , Supryadi , Shaoyang Xu , Haoran Sun , Leiyu Pan , Menglong Cui , Jiangcun Du , Renren Jin , António Branco , Deyi Xiong

Large language models (LLMs) have recently shown remarkable performance in language tasks and beyond. However, due to their limited inherent causal reasoning ability, LLMs still face challenges in handling tasks that require robust causal…

Computation and Language · Computer Science 2025-03-13 Xin Li , Zhuo Cai , Shoujin Wang , Kun Yu , Fang Chen

Large language models (LLMs) process and predict sequences containing text to answer questions, and address tasks including document summarization, providing recommendations, writing software and solving quantitative problems. We provide a…

Numerical Analysis · Mathematics 2026-02-02 Ricardo Baptista , Andrew Stuart , Son Tran

Large Language Models (LLMs) have revolutionized both general natural language processing and domain-specific applications such as code synthesis, legal reasoning, and finance. However, while prior studies have explored individual model…

Software Engineering · Computer Science 2025-12-05 Gunjan Das , Paheli Bhattacharya , Rishabh Gupta

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

The increasing development of LLMs in code generation has drawn significant attention among researchers. To enhance LLM-based code generation ability, current efforts are predominantly directed towards collecting high-quality datasets and…