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Random Number Generation Tasks (RNGTs) are used in psychology for examining how humans generate sequences devoid of predictable patterns. By adapting an existing human RNGT for an LLM-compatible environment, this preliminary study tests…

Artificial Intelligence · Computer Science 2024-08-21 Rachel M. Harrison

Citation Text Generation (CTG) is a task in natural language processing (NLP) that aims to produce text that accurately cites or references a cited document within a source document. In CTG, the generated text draws upon contextual cues…

Computation and Language · Computer Science 2024-04-16 Avinash Anand , Mohit Gupta , Kritarth Prasad , Ujjwal Goel , Naman Lal , Astha Verma , Rajiv Ratn Shah

Large Language Models (LLMs) have revolutionized the field of Natural Language Generation (NLG) by demonstrating an impressive ability to generate human-like text. However, their widespread usage introduces challenges that necessitate…

Computation and Language · Computer Science 2024-06-28 Sara Abdali , Richard Anarfi , CJ Barberan , Jia He

Large language models (LLMs) have shown remarkable success across a wide range of natural language generation tasks, where proper prompt designs make great impacts. While existing prompting methods are normally restricted to providing…

Computation and Language · Computer Science 2023-06-01 Bei Li , Rui Wang , Junliang Guo , Kaitao Song , Xu Tan , Hany Hassan , Arul Menezes , Tong Xiao , Jiang Bian , JingBo Zhu

Machine generated text is increasingly difficult to distinguish from human authored text. Powerful open-source models are freely available, and user-friendly tools that democratize access to generative models are proliferating. ChatGPT,…

Computation and Language · Computer Science 2023-05-09 Evan Crothers , Nathalie Japkowicz , Herna Viktor

Large language models (LLMs) have attracted great attention given their strong performance on a wide range of NLP tasks. In practice, users often expect generated texts to fall within a specific length range, making length controlled…

Computation and Language · Computer Science 2024-06-18 Renlong Jie , Xiaojun Meng , Lifeng Shang , Xin Jiang , Qun Liu

Large Language Models (LLMs) employ three popular training approaches: Masked Language Models (MLM), Causal Language Models (CLM), and Sequence-to-Sequence Models (seq2seq). However, each approach has its strengths and limitations, and…

Machine Learning · Computer Science 2025-02-18 Xuefeng Liu , Songhao Jiang , Bo Li , Rick Stevens

Since language models produce fake text quickly and easily, there is an oversupply of such content in the public domain. The degree of sophistication and writing style has reached a point where differentiating between human authored and…

Computation and Language · Computer Science 2024-02-06 Dmytro Valiaiev

Conversational agents based on Large Language Models (LLMs) have recently emerged as powerful tools for human-computer interaction. Nevertheless, their black-box nature implies challenges in predictability and a lack of personalization,…

Computation and Language · Computer Science 2026-04-07 Barbara Gendron , Gaël Guibon , Mathieu d'Aquin

As Large Language Models (LLMs) and other forms of Generative AI permeate various aspects of our lives, their application for learning and education has provided opportunities and challenges. This paper presents an investigation into the…

Computers and Society · Computer Science 2023-06-06 Daniel Leiker , Sara Finnigan , Ashley Ricker Gyllen , Mutlu Cukurova

Citation generation aims to generate a citation sentence that refers to a chosen paper in the context of a manuscript. However, a rigid citation generation process is at odds with an author's desire to control specific attributes, such as…

Computation and Language · Computer Science 2023-12-15 Nianlong Gu , Richard H. R. Hahnloser

The increasing prevalence of Large Language Models (LMs) in critical applications highlights the need for controlled language generation strategies that are not only computationally efficient but that also enjoy performance guarantees. To…

Computation and Language · Computer Science 2026-03-16 Emily Cheng , Carmen Amo Alonso

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-scale language models, like ChatGPT, have garnered significant media attention and stunned the public with their remarkable capacity for generating coherent text from short natural language prompts. In this paper, we aim to conduct a…

Computation and Language · Computer Science 2024-12-11 Dongqi Liu , Vera Demberg

Despite the crucial importance of accelerating text generation in large language models (LLMs) for efficiently producing content, the sequential nature of this process often leads to high inference latency, posing challenges for real-time…

Computation and Language · Computer Science 2024-05-27 Mahsa Khoshnoodi , Vinija Jain , Mingye Gao , Malavika Srikanth , Aman Chadha

Controlling the attribute intensity of text generation is crucial across scenarios (e.g., writing conciseness, chatting emotion, and explanation clarity). The remarkable capabilities of large language models (LLMs) have revolutionized text…

Computation and Language · Computer Science 2024-06-10 Shang Zhou , Feng Yao , Chengyu Dong , Zihan Wang , Jingbo Shang

Large language models (LLMs) have demonstrated immense potential across various tasks. However, research for exploring and improving the capabilities of LLMs in interpreting graph structures remains limited. To address this gap, we conduct…

Computation and Language · Computer Science 2025-02-17 Jie He , Yijun Yang , Wanqiu Long , Deyi Xiong , Victor Gutierrez-Basulto , Jeff Z. Pan

Advertising text plays a critical role in determining click-through rates (CTR) in online advertising. Large Language Models (LLMs) offer significant efficiency advantages over manual ad text creation. However, LLM-generated ad texts do not…

Information Retrieval · Computer Science 2025-08-05 Yanda Chen , Zihui Ren , Qixiang Gao , Jiale Chen , Si Chen , Xubin Li , Tiezheng Ge , Bo Zheng

To enhance the quality of generated stories, recent story generation models have been investigating the utilization of higher-level attributes like plots or commonsense knowledge. The application of prompt-based learning with large language…

Computation and Language · Computer Science 2023-07-25 Zhuohan Xie , Trevor Cohn , Jey Han Lau

As large-scale language models become the standard for text generation, there is a greater need to tailor the generations to be more or less concise, targeted, and informative, depending on the audience/application. Existing control…

Computation and Language · Computer Science 2024-02-23 Samraj Moorjani , Adit Krishnan , Hari Sundaram