English
Related papers

Related papers: Multimodal Large Language Models to Support Real-W…

200 papers

Recently, Multimodal Large Language Model (MLLM) represented by GPT-4V has been a new rising research hotspot, which uses powerful Large Language Models (LLMs) as a brain to perform multimodal tasks. The surprising emergent capabilities of…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Shukang Yin , Chaoyou Fu , Sirui Zhao , Ke Li , Xing Sun , Tong Xu , Enhong Chen

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

The dissemination of false information on online platforms presents a serious societal challenge. While manual fact-checking remains crucial, Large Language Models (LLMs) offer promising opportunities to support fact-checkers with their…

Computation and Language · Computer Science 2024-10-31 Ivan Vykopal , Matúš Pikuliak , Simon Ostermann , Marián Šimko

Large Language Models (LLMs) hold significant potential for advancing fact-checking by leveraging their capabilities in reasoning, evidence retrieval, and explanation generation. However, existing benchmarks fail to comprehensively evaluate…

Computation and Language · Computer Science 2025-06-17 Shuo Yang , Yuqin Dai , Guoqing Wang , Xinran Zheng , Jinfeng Xu , Jinze Li , Zhenzhe Ying , Weiqiang Wang , Edith C. H. Ngai

The proliferation of disinformation, particularly in multimodal contexts combining text and images, presents a significant challenge across digital platforms. This study investigates the potential of large multimodal models (LMMs) in…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Yasmina Kheddache , Marc Lalonde

In our era of widespread false information, human fact-checkers often face the challenge of duplicating efforts when verifying claims that may have already been addressed in other countries or languages. As false information transcends…

Computation and Language · Computer Science 2025-09-25 Ivan Vykopal , Matúš Pikuliak , Simon Ostermann , Tatiana Anikina , Michal Gregor , Marián Šimko

The increasing proliferation of misinformation and its alarming impact have motivated both industry and academia to develop approaches for misinformation detection and fact checking. Recent advances on large language models (LLMs) have…

Computation and Language · Computer Science 2024-07-22 Sahar Tahmasebi , Eric Müller-Budack , Ralph Ewerth

Recently, Large Language Models (LLMs) have drawn significant attention due to their outstanding reasoning capabilities and extensive knowledge repository, positioning them as superior in handling various natural language processing tasks…

Computation and Language · Computer Science 2023-11-30 Han Cao , Lingwei Wei , Mengyang Chen , Wei Zhou , Songlin Hu

Large multimodal language models (MLLMs) such as GPT-4V and GPT-4o have achieved remarkable advancements in understanding and generating multimodal content, showcasing superior quality and capabilities across diverse tasks. However, their…

Computer Vision and Pattern Recognition · Computer Science 2025-01-09 Xuelu Feng , Yunsheng Li , Dongdong Chen , Mei Gao , Mengchen Liu , Junsong Yuan , Chunming Qiao

The increasing prevalence of online misinformation has heightened the demand for automated fact-checking solutions. Large Language Models (LLMs) have emerged as potential tools for assisting in this task, but their effectiveness remains…

Computers and Society · Computer Science 2025-03-10 Nicolo' Fontana , Francesco Corso , Enrico Zuccolotto , Francesco Pierri

Large vision-language models (LVLMs) have significantly improved multimodal reasoning tasks, such as visual question answering and image captioning. These models embed multimodal facts within their parameters, rather than relying on…

Computation and Language · Computer Science 2025-02-18 Shengkang Wang , Hongzhan Lin , Ziyang Luo , Zhen Ye , Guang Chen , Jing Ma

The remarkable advancements in Multimodal Large Language Models (MLLMs) have not rendered them immune to challenges, particularly in the context of handling deceptive information in prompts, thus producing hallucinated responses under such…

Computer Vision and Pattern Recognition · Computer Science 2024-07-24 Yusu Qian , Haotian Zhang , Yinfei Yang , Zhe Gan

Large Language Models (LLMs) are able to provide assistance on a wide range of information-seeking tasks. However, model outputs may be misleading, whether unintentionally or in cases of intentional deception. We investigate the ability of…

Computation and Language · Computer Science 2024-07-17 Betty Li Hou , Kejian Shi , Jason Phang , James Aung , Steven Adler , Rosie Campbell

By integrating the perception capabilities of multimodal encoders with the generative power of Large Language Models (LLMs), Multimodal Large Language Models (MLLMs), exemplified by GPT-4V, have achieved great success in various multimodal…

Computer Vision and Pattern Recognition · Computer Science 2025-08-18 Wenbin An , Jiahao Nie , Yaqiang Wu , Feng Tian , Shijian Lu , Qinghua Zheng

The proliferation of misinformation necessitates scalable, automated fact-checking solutions. Yet, current benchmarks often overlook multilingual and topical diversity. This paper introduces a novel, dynamically extensible data set that…

Computers and Society · Computer Science 2025-10-22 Lorraine Saju , Arnim Bleier , Jana Lasser , Claudia Wagner

In this paper, we explore the challenges associated with establishing an end-to-end fact-checking pipeline in a real-world context, covering over 90 languages. Our real-world experimental benchmarks demonstrate that fine-tuning Transformer…

Computation and Language · Computer Science 2024-05-01 Vinay Setty

Large Language Models (LLMs) are increasingly used for accessing information on the web. Their truthfulness and factuality are thus of great interest. To help users make the right decisions about the information they get, LLMs should not…

Computation and Language · Computer Science 2024-04-03 Chenglei Si , Navita Goyal , Sherry Tongshuang Wu , Chen Zhao , Shi Feng , Hal Daumé , Jordan Boyd-Graber

Multimodal Large Language Models (MLLMs) are gaining increasing popularity in both academia and industry due to their remarkable performance in various applications such as visual question answering, visual perception, understanding, and…

Computation and Language · Computer Science 2024-09-09 Jian Li , Weiheng Lu , Hao Fei , Meng Luo , Ming Dai , Min Xia , Yizhang Jin , Zhenye Gan , Ding Qi , Chaoyou Fu , Ying Tai , Wankou Yang , Yabiao Wang , Chengjie Wang

Large language models (LLMs), especially when instruction-tuned for chat, have become part of our daily lives, freeing people from the process of searching, extracting, and integrating information from multiple sources by offering a…

Computation and Language · Computer Science 2024-11-01 Yuxia Wang , Minghan Wang , Muhammad Arslan Manzoor , Fei Liu , Georgi Georgiev , Rocktim Jyoti Das , Preslav Nakov

Large vision-language models (LVLMs) have demonstrated remarkable achievements, yet the generation of non-factual responses remains prevalent in fact-seeking question answering (QA). Current multimodal fact-seeking benchmarks primarily…

Computation and Language · Computer Science 2025-03-11 Yanling Wang , Yihan Zhao , Xiaodong Chen , Shasha Guo , Lixin Liu , Haoyang Li , Yong Xiao , Jing Zhang , Qi Li , Ke Xu
‹ Prev 1 2 3 10 Next ›