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While multimodal large language models (MLLMs) have demonstrated extraordinary vision-language understanding capabilities, their abilities to solve instance-level visual-language problems beyond a single image warrant further exploration.…

Computer Vision and Pattern Recognition · Computer Science 2025-07-23 Yunqiu Xu , Linchao Zhu , Yi Yang

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

Large language models (LLMs), such as ChatGPT released by OpenAI, have attracted significant attention from both industry and academia due to their demonstrated ability to generate high-quality content for various tasks. Despite the…

Software Engineering · Computer Science 2024-11-08 Xiaodan Xu , Chao Ni , Xinrong Guo , Shaoxuan Liu , Xiaoya Wang , Kui Liu , Xiaohu Yang

In the era dominated by information overload and its facilitation with Large Language Models (LLMs), the prevalence of misinformation poses a significant threat to public discourse and societal well-being. A critical concern at present…

Computation and Language · Computer Science 2024-11-05 Cem Üyük , Danica Rovó , Shaghayegh Kolli , Rabia Varol , Georg Groh , Daryna Dementieva

In today's digital era, the rapid spread of misinformation poses threats to public well-being and societal trust. As online misinformation proliferates, manual verification by fact checkers becomes increasingly challenging. We introduce…

Computation and Language · Computer Science 2023-10-16 Eun Cheol Choi , Emilio Ferrara

The use of machine learning (ML) models to assess and score textual data has become increasingly pervasive in an array of contexts including natural language processing, information retrieval, search and recommendation, and credibility…

Computation and Language · Computer Science 2023-09-27 Marialena Bevilacqua , Kezia Oketch , Ruiyang Qin , Will Stamey , Xinyuan Zhang , Yi Gan , Kai Yang , Ahmed Abbasi

The efficacy of detectors for texts generated by large language models (LLMs) substantially depends on the availability of large-scale training data. However, white-box zero-shot detectors, which require no such data, are limited by the…

Computation and Language · Computer Science 2025-03-04 Junchao Wu , Runzhe Zhan , Derek F. Wong , Shu Yang , Xuebo Liu , Lidia S. Chao , Min Zhang

With the rapid progress of large language models (LLMs) and the huge amount of text they generated, it becomes more and more impractical to manually distinguish whether a text is machine-generated. Given the growing use of LLMs in social…

Computation and Language · Computer Science 2023-06-12 Jinyan Su , Terry Yue Zhuo , Di Wang , Preslav Nakov

We present MGTEVAL, an extensible platform for systematic evaluation of Machine-Generated Text (MGT) detectors. Despite rapid progress in MGT detection, existing evaluations are often fragmented across datasets, preprocessing, attacks, and…

Cryptography and Security · Computer Science 2026-04-29 Yuanfan Li , Qi Zhou , Chengzhengxu Li , Zhaohan Zhang , Chenxu Zhao , Zepu Ruan , Chao Shen , Xiaoming Liu

Automated fact-checking, using machine learning to verify claims, has grown vital as misinformation spreads beyond human fact-checking capacity. Large Language Models (LLMs) like GPT-4 are increasingly trusted to write academic papers,…

Computation and Language · Computer Science 2024-02-08 Dorian Quelle , Alexandre Bovet

As the field of Large Language Models (LLMs) evolves at an accelerated pace, the critical need to assess and monitor their performance emerges. We introduce a benchmarking framework focused on knowledge graph engineering (KGE) accompanied…

Artificial Intelligence · Computer Science 2023-09-01 Lars-Peter Meyer , Johannes Frey , Kurt Junghanns , Felix Brei , Kirill Bulert , Sabine Gründer-Fahrer , Michael Martin

Large Language Models (LLMs) have demonstrated a powerful ability for text generation. However, achieving optimal results with a given prompt or instruction can be challenging, especially for billion-sized models. Additionally, undesired…

Computation and Language · Computer Science 2024-10-07 Lifu Tu , Semih Yavuz , Jin Qu , Jiacheng Xu , Rui Meng , Caiming Xiong , Yingbo Zhou

Due to the recent improvements and wide availability of Large Language Models (LLMs), they have posed a serious threat to academic integrity in education. Modern LLM-generated text detectors attempt to combat the problem by offering…

Computation and Language · Computer Science 2023-07-17 Michael Sheinman Orenstrakh , Oscar Karnalim , Carlos Anibal Suarez , Michael Liut

The impressive ability of large language models to generate natural text across various tasks has led to critical challenges in authorship authentication. Although numerous detection methods have been developed to differentiate between…

Computation and Language · Computer Science 2025-05-20 Xu Zheng , Zhuomin Chen , Esteban Schafir , Sipeng Chen , Hojat Allah Salehi , Haifeng Chen , Farhad Shirani , Wei Cheng , Dongsheng Luo

Large Language Models (LLMs) can generate highly persuasive text, raising concerns about their misuse for propaganda, manipulation, and other harmful purposes. This leads us to our central question: Is LLM-generated persuasion more…

Computation and Language · Computer Science 2026-04-22 Arkadiusz Modzelewski , Paweł Golik , Anna Kołos , Giovanni Da San Martino

The rapid advancement of large language models (LLMs) has led to increasingly human-like AI-generated text, raising concerns about content authenticity, misinformation, and trustworthiness. Addressing the challenge of reliably detecting…

The detection of machine-generated text, especially from large language models (LLMs), is crucial in preventing serious social problems resulting from their misuse. Some methods train dedicated detectors on specific datasets but fall short…

Machine Learning · Computer Science 2024-06-05 Yibo Miao , Hongcheng Gao , Hao Zhang , Zhijie Deng

Large language models (LLMs) have sparked growing interest in machine learning research agents that can autonomously propose ideas and conduct experiments. However, existing benchmarks predominantly adopt an engineering-oriented…

Computation and Language · Computer Science 2026-02-26 Qiran Zou , Hou Hei Lam , Wenhao Zhao , Yiming Tang , Tingting Chen , Samson Yu , Tianyi Zhang , Chang Liu , Xiangyang Ji , Dianbo Liu

Large Language Models (LLMs) are now capable of generating text that closely resembles human writing, making them powerful tools for content creation, but this growing ability has also made it harder to tell whether a piece of text was…

Computation and Language · Computer Science 2025-10-21 Muhammad Ammar , Hadiya Murad Hadi , Usman Majeed Butt

Multimodal large language models (MLLMs) carry the potential to support humans in processing vast amounts of information. While MLLMs are already being used as a fact-checking tool, their abilities and limitations in this regard are…

Computation and Language · Computer Science 2024-04-29 Jiahui Geng , Yova Kementchedjhieva , Preslav Nakov , Iryna Gurevych
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