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While factual correctness and task-performance have been in focus of Large Language Model (LLM) research for a long time, the fundamental question of how human-like generated texts are on a linguistic level has been underexplored. From a…

Computation and Language · Computer Science 2026-05-27 Björn Nieth , Marianna Gracheva , Michaela Mahlberg , Bjoern Eskofier , Emmanuelle Salin

The rapid advancements in large language models (LLMs) have significantly improved their ability to generate natural language, making texts generated by LLMs increasingly indistinguishable from human-written texts. Recent research has…

Computation and Language · Computer Science 2024-12-05 Sergio E. Zanotto , Segun Aroyehun

This article presents two corpora of English and Czech texts generated with large language models (LLMs). The motivation is to create a resource for comparing human-written texts with LLM-generated text linguistically. Emphasis was placed…

Computation and Language · Computer Science 2025-11-11 Jiří Milička , Anna Marklová , Václav Cvrček

Large Language Models (LLMs) are now capable of generating highly fluent, human-like text. They enable many applications, but also raise concerns such as large scale spam, phishing, or academic misuse. While much work has focused on…

Computation and Language · Computer Science 2026-04-16 Swati Rallapalli , Shannon Gallagher , Ronald Yurko , Tyler Brooks , Chuck Loughin , Michele Sezgin , Violet Turri

The rapid advancements in large language models (LLMs) have significantly improved their ability to generate natural language, making texts generated by LLMs increasingly indistinguishable from human-written texts. While recent research has…

Computation and Language · Computer Science 2025-10-01 Sergio E. Zanotto , Segun Aroyehun

The development and evaluation of Large Language Models (LLMs) has primarily focused on their task-solving capabilities, with recent models even surpassing human performance in some areas. However, this focus often neglects whether…

Computation and Language · Computer Science 2025-07-29 Yanzhu Guo , Guokan Shang , Chloé Clavel

Large language models (LLMs) are capable of writing grammatical text that follows instructions, answers questions, and solves problems. As they have advanced, it has become difficult to distinguish their output from human-written text.…

Computation and Language · Computer Science 2025-08-25 Alex Reinhart , Ben Markey , Michael Laudenbach , Kachatad Pantusen , Ronald Yurko , Gordon Weinberg , David West Brown

This paper introduces a framework for the automated evaluation of natural language texts. A manually constructed rubric describes how to assess multiple dimensions of interest. To evaluate a text, a large language model (LLM) is prompted…

Computation and Language · Computer Science 2025-01-03 Helia Hashemi , Jason Eisner , Corby Rosset , Benjamin Van Durme , Chris Kedzie

The potential of artificial intelligence (AI)-based large language models (LLMs) holds considerable promise in revolutionizing education, research, and practice. However, distinguishing between human-written and AI-generated text has become…

Computation and Language · Computer Science 2023-11-14 Kadhim Hayawi , Sakib Shahriar , Sujith Samuel Mathew

Large Language Models (LLMs) represent a major step toward artificial general intelligence, significantly advancing our ability to interact with technology. While LLMs perform well on Natural Language Processing tasks -- such as…

Computation and Language · Computer Science 2025-05-15 Brandon Smith , Mohamed Reda Bouadjenek , Tahsin Alamgir Kheya , Phillip Dawson , Sunil Aryal

We conduct a quantitative analysis contrasting human-written English news text with comparable large language model (LLM) output from six different LLMs that cover three different families and four sizes in total. Our analysis spans several…

Computation and Language · Computer Science 2024-09-04 Alberto Muñoz-Ortiz , Carlos Gómez-Rodríguez , David Vilares

In recent years, researchers have proposed numerous benchmarks to evaluate the impressive coding capabilities of large language models (LLMs). However, current benchmarks primarily assess the accuracy of LLM-generated code, while neglecting…

Software Engineering · Computer Science 2024-10-10 Jiasheng Zheng , Boxi Cao , Zhengzhao Ma , Ruotong Pan , Hongyu Lin , Yaojie Lu , Xianpei Han , Le Sun

Current benchmarks for evaluating Large Language Models (LLMs) often do not exhibit enough writing style diversity, with many adhering primarily to standardized conventions. Such benchmarks do not fully capture the rich variety of…

Computation and Language · Computer Science 2025-09-29 Kimberly Le Truong , Riccardo Fogliato , Hoda Heidari , Zhiwei Steven Wu

The rapid evolution of Multimodal Large Language Models (MLLMs) has brought substantial advancements in artificial intelligence, significantly enhancing the capability to understand and generate multimodal content. While prior studies have…

Artificial Intelligence · Computer Science 2024-09-30 Lin Li , Guikun Chen , Hanrong Shi , Jun Xiao , Long Chen

The paper explores stylometry as a method to distinguish between texts created by Large Language Models (LLMs) and humans, addressing issues of model attribution, intellectual property, and ethical AI use. Stylometry has been used…

Computation and Language · Computer Science 2025-07-25 Karol Przystalski , Jan K. Argasiński , Iwona Grabska-Gradzińska , Jeremi K. Ochab

The degree to which large language models (LLMs) produce writing that is truly human-like remains unclear despite the extensive empirical attention that this question has received. The present study addresses this question from the…

Computation and Language · Computer Science 2026-01-27 Kelly Kendro , Jeffrey Maloney , Scott Jarvis

The rapid advancement of large language models (LLMs) has made detecting AI-generated text an increasingly critical challenge. Traditional methods often fail to capture the nuanced semantic differences between human and machine-generated…

Computation and Language · Computer Science 2025-02-03 Lifu Gao , Ziwei Liu , Qi Zhang

Large language models (LLMs) have transformed human writing by enhancing grammar correction, content expansion, and stylistic refinement. However, their widespread use raises concerns about authorship, originality, and ethics, even…

Computation and Language · Computer Science 2024-10-21 Zhen Tao , Zhiyu Li , Runyu Chen , Dinghao Xi , Wei Xu

Large language models (LLMs) have gained significant attention due to their ability to mimic human language. Identifying texts generated by LLMs is crucial for understanding their capabilities and mitigating potential consequences. This…

Computation and Language · Computer Science 2024-07-19 Anjali Rawal , Hui Wang , Youjia Zheng , Yu-Hsuan Lin , Shanu Sushmita

The recent large language models (LLMs), e.g., ChatGPT, have been able to generate human-like and fluent responses when provided with specific instructions. While admitting the convenience brought by technological advancement, educators…

Computation and Language · Computer Science 2023-12-27 Zijie Zeng , Lele Sha , Yuheng Li , Kaixun Yang , Dragan Gašević , Guanliang Chen
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