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While state-of-the-art large language models (LLMs) have shown impressive performance on many tasks, there has been extensive research on undesirable model behavior such as hallucinations and bias. In this work, we investigate how the…

Computation and Language · Computer Science 2025-11-07 Elinor Poole-Dayan , Deb Roy , Jad Kabbara

Detecting disinformation that blends manipulated text and images has become increasingly challenging, as AI tools make synthetic content easy to generate and disseminate. While most existing AI safety benchmarks focus on single modality…

Large Language Models (LLMs) have the potential to enhance Agent-Based Modeling by better representing complex interdependent cybersecurity systems, improving cybersecurity threat modeling and risk management. However, evaluating LLMs in…

Cryptography and Security · Computer Science 2024-06-12 Tam n. Nguyen

With the evolution of large language models (LLMs), their robustness against individual simple biases has been enhanced. However, we observe that the ensemble of multiple simple biases still exerts a significant adverse impact on LLMs.…

Computation and Language · Computer Science 2026-04-21 Zhouhao Sun , Zhiyuan Kan , Xiao Ding , Li Du , Bibo Cai , Yang Zhao , Bing Qin , Ting Liu

Honesty is a fundamental principle for aligning large language models (LLMs) with human values, requiring these models to recognize what they know and don't know and be able to faithfully express their knowledge. Despite promising, current…

Computation and Language · Computer Science 2024-09-30 Siheng Li , Cheng Yang , Taiqiang Wu , Chufan Shi , Yuji Zhang , Xinyu Zhu , Zesen Cheng , Deng Cai , Mo Yu , Lemao Liu , Jie Zhou , Yujiu Yang , Ngai Wong , Xixin Wu , Wai Lam

The most effective misinformation campaigns are multimodal, often combining text with images and videos taken out of context -- or fabricating them entirely -- to support a given narrative. Contemporary methods for detecting misinformation,…

Computation and Language · Computer Science 2025-02-17 Tomas Peterka , Matyas Bohacek

Large Language Models (LLMs) excel at producing broadly relevant text, but this generality becomes a limitation when user-specific preferences are required, such as recommending restaurants or planning travel. In these scenarios, users…

Machine Learning · Computer Science 2025-10-21 Ioannis Tsaknakis , Bingqing Song , Shuyu Gan , Dongyeop Kang , Alfredo Garcia , Gaowen Liu , Charles Fleming , Mingyi Hong

News recommender systems play a critical role in mitigating the information overload problem. In recent years, due to the successful applications of large language model technologies, researchers have utilized Discriminative Large Language…

Information Retrieval · Computer Science 2025-02-25 Rongyao Wang , Veronica Liesaputra , Zhiyi Huang

Large language models (LLMs) have attracted growing interest as supportive tools for psychiatric assessment and clinical decision support. However, existing mental health benchmarks largely rely on social media data or supportive dialogue…

Computation and Language · Computer Science 2026-05-19 Hoyun Song , Migyeong Kang , Jisu Shin , Jihyun Kim , Chanbi Park , Hangyeol Yoo , Jihyun An , Alice Oh , Jinyoung Han , KyungTae Lim

The rapid growth of social media has resulted in an explosion of online news content, leading to a significant increase in the spread of misleading or false information. While machine learning techniques have been widely applied to detect…

Computation and Language · Computer Science 2024-12-10 Hao Chen , Hui Guo , Baochen Hu , Shu Hu , Jinrong Hu , Siwei Lyu , Xi Wu , Xin Wang

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

Recently Multimodal Large Language Models (MLLMs) have achieved considerable advancements in vision-language tasks, yet produce potentially harmful or untrustworthy content. Despite substantial work investigating the trustworthiness of…

Artificial Intelligence · Computer Science 2026-01-14 Yanxu Zhu , Shitong Duan , Xiangxu Zhang , Jitao Sang , Peng Zhang , Tun Lu , Xiao Zhou , Jing Yao , Xiaoyuan Yi , Xing Xie

Large Language Models (LLMs) have garnered significant attention due to their remarkable ability to process information across various languages. Despite their capabilities, they exhibit inconsistencies in handling identical queries in…

Computation and Language · Computer Science 2024-06-24 Yue Huang , Chenrui Fan , Yuan Li , Siyuan Wu , Tianyi Zhou , Xiangliang Zhang , Lichao Sun

As Large Language Model (LLM) agents become more widespread, associated misalignment risks increase. While prior research has studied agents' ability to produce harmful outputs or follow malicious instructions, it remains unclear how likely…

Large Language Models (LLMs) have shown impressive capabilities in various applications, but they still face various inconsistency issues. Existing works primarily focus on the inconsistency issues within a single LLM, while we…

Computation and Language · Computer Science 2024-11-15 Kai Xiong , Xiao Ding , Yixin Cao , Ting Liu , Bing Qin

Most of the existing Large Language Model (LLM) benchmarks on scientific problem reasoning focus on problems grounded in high-school subjects and are confined to elementary algebraic operations. To systematically examine the reasoning…

Computation and Language · Computer Science 2024-07-01 Xiaoxuan Wang , Ziniu Hu , Pan Lu , Yanqiao Zhu , Jieyu Zhang , Satyen Subramaniam , Arjun R. Loomba , Shichang Zhang , Yizhou Sun , Wei Wang

Fake news undermines societal trust and decision-making across politics, economics, health, and international relations, and in extreme cases threatens human lives and societal safety. Because fake news reflects region-specific political,…

Machine Learning · Computer Science 2026-03-03 Masahiro Kaneko , Ayana Niwa , Timothy Baldwin

Fact checking can be an effective strategy against misinformation, but its implementation at scale is impeded by the overwhelming volume of information online. Recent artificial intelligence (AI) language models have shown impressive…

Human-Computer Interaction · Computer Science 2025-05-23 Matthew R. DeVerna , Harry Yaojun Yan , Kai-Cheng Yang , Filippo Menczer

Large language models (LLMs) have recently shown impressive performance on tasks involving reasoning, leading to a lively debate on whether these models possess reasoning capabilities similar to humans. However, despite these successes, the…

Computation and Language · Computer Science 2024-08-07 Philipp Mondorf , Barbara Plank

Large Language Models (LLMs) are a transformational technology, fundamentally changing how people obtain information and interact with the world. As people become increasingly reliant on them for an enormous variety of tasks, a body of…

Computers and Society · Computer Science 2025-05-08 Nouar Aldahoul , Hazem Ibrahim , Matteo Varvello , Aaron Kaufman , Talal Rahwan , Yasir Zaki