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Large language models (LLMs) exhibit remarkable capabilities across diverse tasks, yet aligning them efficiently and effectively with human expectations remains a critical challenge. This thesis advances LLM alignment by introducing novel…

Computation and Language · Computer Science 2025-06-12 Yuxin Jiang

Human decision-making belongs to the foundation of our society and civilization, but we are on the verge of a future where much of it will be delegated to artificial intelligence. The arrival of Large Language Models (LLMs) has transformed…

Artificial Intelligence · Computer Science 2025-06-23 Hao Li , Gengrui Zhang , Petter Holme , Shuyue Hu , Zhen Wang

Large Language Models (LLMs) have transformed artificial intelligence by excelling in complex natural language processing tasks. Their ability to generate human-like text has opened new possibilities for market research, particularly in…

Artificial Intelligence · Computer Science 2026-04-20 Mengxin Wang , Dennis J. Zhang , Heng Zhang

Large language models (LLMs) offer emerging opportunities for psychological and behavioral research, but methodological guidance is lacking. This article provides a framework for using LLMs as psychological simulators across two primary…

Computers and Society · Computer Science 2026-04-07 Zhicheng Lin

Big models, exemplified by Large Language Models (LLMs), are models typically pre-trained on massive data and comprised of enormous parameters, which not only obtain significantly improved performance across diverse tasks but also present…

Artificial Intelligence · Computer Science 2023-09-06 Jing Yao , Xiaoyuan Yi , Xiting Wang , Jindong Wang , Xing Xie

This paper explores the advancements in making large language models (LLMs) more human-like. We focus on techniques that enhance natural language understanding, conversational coherence, and emotional intelligence in AI systems. The study…

Computation and Language · Computer Science 2026-02-03 Ethem Yağız Çalık , Talha Rüzgar Akkuş

Machine learning practitioners often face significant challenges in formally integrating their prior knowledge and beliefs into predictive models, limiting the potential for nuanced and context-aware analyses. Moreover, the expertise needed…

Machine Learning · Statistics 2024-12-23 James Requeima , John Bronskill , Dami Choi , Richard E. Turner , David Duvenaud

The rapid development of Large Language Models (LLMs) demonstrates remarkable multilingual capabilities in natural language processing, attracting global attention in both academia and industry. To mitigate potential discrimination and…

Computation and Language · Computer Science 2025-01-08 Kaiyu Huang , Fengran Mo , Xinyu Zhang , Hongliang Li , You Li , Yuanchi Zhang , Weijian Yi , Yulong Mao , Jinchen Liu , Yuzhuang Xu , Jinan Xu , Jian-Yun Nie , Yang Liu

In recent years, large language models (LLMs) have achieved remarkable success in natural language processing (NLP). LLMs require an extreme amount of parameters to attain high performance. As models grow into the trillion-parameter range,…

Computation and Language · Computer Science 2024-09-10 Zhyar Rzgar K Rostam , Sándor Szénási , Gábor Kertész

Large Language Models(LLMs)have become effective tools for natural language processing and have been used in many different fields. This essay offers a succinct summary of various LLM subcategories. The survey emphasizes recent developments…

Computation and Language · Computer Science 2023-07-21 Saurabh Pahune , Manoj Chandrasekharan

With the capabilities of understanding and executing natural language instructions, Large language models (LLMs) can potentially act as a powerful tool for textual data augmentation. However, the quality of augmented data depends heavily on…

Computation and Language · Computer Science 2024-04-30 Yichuan Li , Kaize Ding , Jianling Wang , Kyumin Lee

Large Language Models (LLMs) have drawn a lot of attention due to their strong performance on a wide range of natural language tasks, since the release of ChatGPT in November 2022. LLMs' ability of general-purpose language understanding and…

Computation and Language · Computer Science 2025-03-25 Shervin Minaee , Tomas Mikolov , Narjes Nikzad , Meysam Chenaghlu , Richard Socher , Xavier Amatriain , Jianfeng Gao

Large language models (LLMs) have achieved remarkable capabilities across diverse tasks, yet their internal decision-making processes remain largely opaque. Mechanistic interpretability (i.e., the systematic study of how neural networks…

Computation and Language · Computer Science 2026-02-13 Usman Naseem

As research in human-centered NLP advances, there is a growing recognition of the importance of incorporating human and social factors into NLP models. At the same time, our NLP systems have become heavily reliant on LLMs, most of which do…

Computation and Language · Computer Science 2025-07-21 Nikita Soni , H. Andrew Schwartz , João Sedoc , Niranjan Balasubramanian

Large Language Models (LLMs) have emerged as powerful tools in the field of Natural Language Processing (NLP) and have recently gained significant attention in the domain of Recommendation Systems (RS). These models, trained on massive…

Information Retrieval · Computer Science 2024-06-19 Likang Wu , Zhi Zheng , Zhaopeng Qiu , Hao Wang , Hongchao Gu , Tingjia Shen , Chuan Qin , Chen Zhu , Hengshu Zhu , Qi Liu , Hui Xiong , Enhong Chen

Large Language Models (LLMs) have shown capabilities close to human performance in various analytical tasks, leading researchers to use them for time and labor-intensive analyses. However, their capability to handle highly specialized and…

Computation and Language · Computer Science 2024-10-08 Alexander S. Choi , Syeda Sabrina Akter , JP Singh , Antonios Anastasopoulos

Large Language Models (LLMs) acquire extensive knowledge and remarkable abilities from extensive text corpora, making them powerful tools for various applications. To make LLMs more usable, aligning them with human preferences is essential.…

Computation and Language · Computer Science 2024-10-21 Mozhi Zhang , Pengyu Wang , Chenkun Tan , Mianqiu Huang , Dong Zhang , Yaqian Zhou , Xipeng Qiu

Recent advancements in Large Language Models (LLMs) have brought them closer to matching human cognition across a variety of tasks. How well do these models align with human performance in detecting and mapping analogies? Prior research has…

Computation and Language · Computer Science 2025-07-16 Kalit Inani , Keshav Kabra , Vijay Marupudi , Sashank Varma

Large Language Models (LLMs) stand at the forefront of a number of Natural Language Processing (NLP) tasks. Despite the widespread adoption of LLMs in NLP, much of their potential in broader fields remains largely unexplored, and…

Machine Learning · Computer Science 2024-03-11 Zhiqiang Zhong , Kuangyu Zhou , Davide Mottin

Language models (LMs) are machine learning models designed to predict linguistic patterns by estimating the probability of word sequences based on large-scale datasets, such as text. LMs have a wide range of applications in natural language…