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With the increasing reliance on LLMs as research agents, distinguishing between LLM and human-generated ideas has become crucial for understanding the cognitive nuances of LLMs' research capabilities. While detecting LLM-generated text has…

Machine Learning · Computer Science 2025-12-08 Sadat Shahriar , Navid Ayoobi , Arjun Mukherjee

While historical considerations surrounding text authenticity revolved primarily around plagiarism, the advent of large language models (LLMs) has introduced a new challenge: distinguishing human-authored from AI-generated text. This shift…

The advent of Large Language Models (LLMs) has enabled the generation of text that increasingly exhibits human-like characteristics. As the detection of such content is of significant importance, substantial research has been conducted with…

Computation and Language · Computer Science 2025-01-22 Aldan Creo , Shushanta Pudasaini

The advancing fluency of LLMs raises important questions about their ability to emulate complex human traits, including emotional expression and personality, across diverse linguistic and cultural contexts. This study investigates whether…

Computation and Language · Computer Science 2026-03-25 Nasser A Alsadhan

The rapid advancement of large language models (LLMs) such as ChatGPT, DeepSeek, and Claude has significantly increased the presence of AI-generated text in digital communication. This trend has heightened the need for reliable detection…

Computation and Language · Computer Science 2025-10-13 Cong Zeng , Shengkun Tang , Yuanzhou Chen , Zhiqiang Shen , Wenchao Yu , Xujiang Zhao , Haifeng Chen , Wei Cheng , Zhiqiang Xu

The rapid advancement of large language models (LLMs) has made machine-generated text increasingly difficult to distinguish from human-written text. While recent studies explore leveraging internal representations of language models to…

Applications · Statistics 2026-05-14 Luxu Liang , Xiang Li

This paper does not describe a new method; instead, it provides a thorough exploration of an important yet understudied design space related to recent advances in text-to-image synthesis -- specifically, the deep fusion of large language…

Computer Vision and Pattern Recognition · Computer Science 2025-05-16 Bingda Tang , Boyang Zheng , Xichen Pan , Sayak Paul , Saining Xie

Large language models (LLMs) have demonstrated strong performance on formal language tasks, yet whether this reflects genuine symbolic reasoning or pattern matching on familiar constructions remains unclear. We introduce a benchmark for…

Computation and Language · Computer Science 2026-01-21 Shlok Shelat , Jay Raval , Souvik Roy , Manas Gaur

Language Confusion is a phenomenon where Large Language Models (LLMs) generate text that is neither in the desired language, nor in a contextually appropriate language. This phenomenon presents a critical challenge in text generation by…

Computation and Language · Computer Science 2025-02-11 Yiyi Chen , Qiongxiu Li , Russa Biswas , Johannes Bjerva

Large language models (LLMs) are solidifying their position in the modern world as effective tools for the automatic generation of text. Their use is quickly becoming commonplace in fields such as education, healthcare, and scientific…

Computation and Language · Computer Science 2025-10-08 Luka Terčon , Kaja Dobrovoljc

The rapid evolution of the fashion industry increasingly intersects with technological advancements, particularly through the integration of generative AI. This study introduces a novel generative pipeline designed to transform the fashion…

Computer Vision and Pattern Recognition · Computer Science 2024-04-30 Abhishek Kumar Singh , Ioannis Patras

As large language models (LLMs) become more advanced, it is increasingly difficult to distinguish between human-written and AI-generated text. This paper draws a conceptual parallel between quantum uncertainty and the limits of authorship…

Computation and Language · Computer Science 2025-09-16 Aadil Gani Ganie

The advent of instruction-tuned language models that convincingly mimic human writing poses a significant risk of abuse. However, such abuse may be counteracted with the ability to detect whether a piece of text was composed by a language…

Computation and Language · Computer Science 2024-05-09 Rafael Rivera Soto , Kailin Koch , Aleem Khan , Barry Chen , Marcus Bishop , Nicholas Andrews

With the advent of large language models (LLM), the line between human-crafted and machine-generated texts has become increasingly blurred. This paper delves into the inquiry of identifying discernible and unique linguistic properties in…

Computation and Language · Computer Science 2024-06-10 Zae Myung Kim , Kwang Hee Lee , Preston Zhu , Vipul Raheja , Dongyeop Kang

Recent Large Language Models (LLMs) have demonstrated remarkable capabilities in generating text that closely resembles human writing across wide range of styles and genres. However, such capabilities are prone to potential abuse, such as…

Computation and Language · Computer Science 2023-11-09 Harika Abburi , Kalyani Roy , Michael Suesserman , Nirmala Pudota , Balaji Veeramani , Edward Bowen , Sanmitra Bhattacharya

Recent advancements in large language models (LLMs) have significantly improved Natural Language to SQL (NL2SQL) tasks, yet most NL2SQL systems continue to rely on the autoregressive (AR) paradigm. The highly structured nature of SQL makes…

Databases · Computer Science 2026-05-28 Peixian Ma , Xialie Zhuang , Jiantao Tan , Changlun Li , Ruirui Chen , Chengwei Qin

Large language models (LLMs) such as ChatGPT are increasingly being used for various use cases, including text content generation at scale. Although detection methods for such AI-generated text exist already, we investigate ChatGPT's…

Computation and Language · Computer Science 2023-08-21 Amrita Bhattacharjee , Huan Liu

Detecting text generated by large language models (LLMs) is of great recent interest. With zero-shot methods like DetectGPT, detection capabilities have reached impressive levels. However, the reliability of existing detectors in real-world…

Computation and Language · Computer Science 2025-03-13 Junchao Wu , Runzhe Zhan , Derek F. Wong , Shu Yang , Xinyi Yang , Yulin Yuan , Lidia S. Chao

Since the proliferation of LLMs, there have been concerns about their misuse for harmful content creation and spreading. Recent studies justify such fears, providing evidence of LLM vulnerabilities and high potential of their misuse. Humans…

Computation and Language · Computer Science 2025-03-20 Dominik Macko , Robert Moro , Ivan Srba

With the launch of ChatGPT, large language models (LLMs) have attracted global attention. In the realm of article writing, LLMs have witnessed extensive utilization, giving rise to concerns related to intellectual property protection,…

Computation and Language · Computer Science 2024-06-14 Ying Zhou , Ben He , Le Sun
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