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Related papers: AutoML-GPT: Automatic Machine Learning with GPT

200 papers

Recently, program synthesis driven by large language models (LLMs) has become increasingly popular. However, program synthesis for machine learning (ML) tasks still poses significant challenges. This paper explores a novel form of program…

Software Engineering · Computer Science 2024-09-10 Jinglue Xu , Jialong Li , Zhen Liu , Nagar Anthel Venkatesh Suryanarayanan , Guoyuan Zhou , Jia Guo , Hitoshi Iba , Kenji Tei

The advent of large language models (LLMs) has opened up new opportunities in the field of mobile task automation. Their superior language understanding and reasoning capabilities allow users to automate complex and repetitive tasks.…

Human-Computer Interaction · Computer Science 2024-10-17 Sunjae Lee , Junyoung Choi , Jungjae Lee , Munim Hasan Wasi , Hojun Choi , Steven Y. Ko , Sangeun Oh , Insik Shin

Large language models (LLMs) have displayed an impressive ability to harness natural language to perform complex tasks. In this work, we explore whether we can leverage this learned ability to find and explain patterns in data.…

Machine Learning · Computer Science 2023-01-30 Chandan Singh , John X. Morris , Jyoti Aneja , Alexander M. Rush , Jianfeng Gao

By conditioning on natural language instructions, large language models (LLMs) have displayed impressive capabilities as general-purpose computers. However, task performance depends significantly on the quality of the prompt used to steer…

Machine Learning · Computer Science 2023-03-13 Yongchao Zhou , Andrei Ioan Muresanu , Ziwen Han , Keiran Paster , Silviu Pitis , Harris Chan , Jimmy Ba

With the advancements in Large Language Models (LLMs), Vision-Language Models (VLMs) have reached a new level of sophistication, showing notable competence in executing intricate cognition and reasoning tasks. However, existing evaluation…

Computer Vision and Pattern Recognition · Computer Science 2023-11-27 Yuanfeng Ji , Chongjian Ge , Weikai Kong , Enze Xie , Zhengying Liu , Zhengguo Li , Ping Luo

With the development of Large Language Models (LLM), numerous prompts have been proposed, each with a rich set of features and their own merits. This paper summarizes the prompt words for large language models (LLMs), categorizing them into…

Computation and Language · Computer Science 2024-04-17 Chenggian Ma , Xiangyu Zhao , Chunhui Zhang , Yanzhao Qin , Wentao Zhang

Language models have steadily increased in size over the past few years. They achieve a high level of performance on various natural language processing (NLP) tasks such as question answering and summarization. Large language models (LLMs)…

Computation and Language · Computer Science 2023-01-31 Jessica Huynh , Cathy Jiao , Prakhar Gupta , Shikib Mehri , Payal Bajaj , Vishrav Chaudhary , Maxine Eskenazi

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

Generative large language models (LLMs) have demonstrated exceptional proficiency in various natural language processing (NLP) tasks, including machine translation, question answering, text summarization, and natural language understanding.…

Computation and Language · Computer Science 2024-01-17 Nooshin Pourkamali , Shler Ebrahim Sharifi

Pre-trained large language models can efficiently interpolate human-written prompts in a natural way. Multitask prompted learning can help generalization through a diverse set of tasks at once, thus enhancing the potential for more…

Computation and Language · Computer Science 2022-12-22 M Saiful Bari , Aston Zhang , Shuai Zheng , Xingjian Shi , Yi Zhu , Shafiq Joty , Mu Li

Over the last decade, a wide range of training and deployment strategies for Large Language Models (LLMs) have emerged. Among these, the prompting paradigms of Auto-regressive LLMs (AR-LLMs) have catalyzed a significant surge in Artificial…

Computation and Language · Computer Science 2024-05-20 Xinzhe Li , Ming Liu

Large language models (LLMs) have revolutionized a large variety of NLP tasks. An active debate is to what extent they can do reasoning and planning. Prior work has assessed the latter in the specific context of PDDL planning, based on…

Artificial Intelligence · Computer Science 2025-05-05 Katharina Stein , Daniel Fišer , Jörg Hoffmann , Alexander Koller

Generative Large Language Models (gLLMs), such as ChatGPT, are increasingly being used in communication research for content analysis. Studies show that gLLMs can outperform both crowd workers and trained coders, such as research…

Artificial Intelligence · Computer Science 2025-10-29 Daria Kravets-Meinke , Hannah Schmid-Petri , Sonja Niemann , Ute Schmid

Artificial intelligence (AI), particularly in the form of large language models (LLMs) or chatbots, has become increasingly integrated into our daily lives. In the past five years, several LLMs have been introduced, including ChatGPT by…

Human-Computer Interaction · Computer Science 2026-05-06 Mouhacine Benosman

A comprehensive guide to Automated Machine Learning (AutoML) is presented, covering fundamental principles, practical implementations, and future trends. The paper is structured to assist both beginners and experienced practitioners, with…

Large Language Models (LLMs) have recently shown promise as high-level planners for robots when given access to a selection of low-level skills. However, it is often assumed that LLMs do not possess sufficient knowledge to be used for the…

Robotics · Computer Science 2024-06-19 Teyun Kwon , Norman Di Palo , Edward Johns

E-learning environments are increasingly harnessing large language models (LLMs) like GPT-3.5 and GPT-4 for tailored educational support. This study introduces an approach that integrates dynamic knowledge graphs with LLMs to offer nuanced…

Artificial Intelligence · Computer Science 2024-12-06 Patrick Ocheja , Brendan Flanagan , Yiling Dai , Hiroaki Ogata

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

Large language models (LLMs), such as ChatGPT, have received substantial attention due to their capabilities for understanding and generating human language. While there has been a burgeoning trend in research focusing on the employment of…

The field of prompt engineering is becoming an essential phenomenon in artificial intelligence. It is altering how data scientists interact with large language models (LLMs) for analytics applications. This research paper shares empirical…

Digital Libraries · Computer Science 2026-02-03 Snehasish Paul , Rohit Kumar , Laxman Das