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Artificial Intelligence (AI) is increasingly being integrated into scientific research, particularly in the social sciences, where understanding human behavior is critical. Large Language Models (LLMs) have shown promise in replicating…

计算与语言 · 计算机科学 2025-06-23 Ziyan Cui , Ning Li , Huaikang Zhou

Large Language Models (LLMs) have become foundational in modern language-driven software applications, profoundly influencing daily life. A critical technique in leveraging their potential is role-playing, where LLMs simulate diverse roles…

计算机与社会 · 计算机科学 2026-04-23 Xinyue Li , Zhenpeng Chen , Jie M. Zhang , Ying Xiao , Tianlin Li , Weisong Sun , Yang Liu , Yiling Lou , Xuanzhe Liu

Large Language Models (LLMs) have demonstrated notable capabilities across various tasks, showcasing complex problem-solving abilities. Understanding and executing complex rules, along with multi-step planning, are fundamental to logical…

人工智能 · 计算机科学 2024-10-15 Jiayi Gui , Yiming Liu , Jiale Cheng , Xiaotao Gu , Xiao Liu , Hongning Wang , Yuxiao Dong , Jie Tang , Minlie Huang

Neural surrogate models are powerful and efficient tools in data mining. Meanwhile, large language models (LLMs) have demonstrated remarkable capabilities in code-related tasks, such as generation and understanding. However, an equally…

机器学习 · 计算机科学 2026-05-26 Bohan Lyu , Siqiao Huang , Zichen Liang

Large language models (LLMs) are increasingly used in high-stakes settings, where overconfident responses can mislead users. Reliable confidence estimation has been shown to enhance trust and task accuracy. Yet existing methods face…

计算与语言 · 计算机科学 2025-09-30 Linwei Tao , Yi-Fan Yeh , Bo Kai , Minjing Dong , Tao Huang , Tom A. Lamb , Jialin Yu , Philip H. S. Torr , Chang Xu

Large reasoning models (LRMs) have shown significant progress in test-time scaling through chain-of-thought prompting. Current approaches like search-o1 integrate retrieval augmented generation (RAG) into multi-step reasoning processes but…

计算与语言 · 计算机科学 2026-01-21 Kaiwen Wei , Rui Shan , Dongsheng Zou , Jianzhong Yang , Bi Zhao , Junnan Zhu , Jiang Zhong

This paper examines the reasoning capabilities of Large Language Models (LLMs) from a novel perspective, focusing on their ability to operate within formally specified, rule-governed environments. We evaluate four LLMs (Gemini 2.5 Pro and…

人工智能 · 计算机科学 2026-02-24 Maciej Świechowski , Adam Żychowski , Jacek Mańdziuk

Ensuring the verifiability of model answers is a fundamental challenge for retrieval-augmented generation (RAG) in the question answering (QA) domain. Recently, self-citation prompting was proposed to make large language models (LLMs)…

计算与语言 · 计算机科学 2024-12-02 Jirui Qi , Gabriele Sarti , Raquel Fernández , Arianna Bisazza

Large language models (LLMs) excel at solving problems with clear and complete statements, but often struggle with nuanced environments or interactive tasks which are common in most real-world scenarios. This highlights the critical need…

The ongoing revolution in language modeling has led to various novel applications, some of which rely on the emerging social abilities of large language models (LLMs). Already, many turn to the new cyber friends for advice during the…

计算机与社会 · 计算机科学 2025-08-05 Ivan Zakazov , Mikolaj Boronski , Lorenzo Drudi , Robert West

Significant advancements have occurred in the application of Large Language Models (LLMs) for social simulations. Despite this, their abilities to perform teaming in task-oriented social events are underexplored. Such capabilities are…

人工智能 · 计算机科学 2025-08-18 Yuan Li , Lichao Sun , Yixuan Zhang

Appreciating multi-figure paintings requires understanding how characters relate through subtle cues like gaze alignment, gesture, and spatial arrangement. We present MIRAGE, an evidence-centric framework designed to scaffold the…

计算机视觉与模式识别 · 计算机科学 2026-04-28 Jui-Cheng Chiu , Yu-Chao Wang , Shengyang Luo , Tongyan Wang , Qi Yang , Nabin Khanal , Yingjie Victor Chen

Large Language Models (LLMs) demonstrate a notable capacity for adopting personas and engaging in role-playing. However, evaluating this ability presents significant challenges, as human assessments are resource-intensive and automated…

计算与语言 · 计算机科学 2025-05-20 Yassine El Boudouri , Walter Nuninger , Julian Alvarez , Yvan Peter

Large Vision Language Models (LVLMs) have demonstrated remarkable abilities in understanding and reasoning about both visual and textual information. However, existing evaluation methods for LVLMs, primarily based on benchmarks like Visual…

计算机视觉与模式识别 · 计算机科学 2025-03-05 Xinyu Wang , Bohan Zhuang , Qi Wu

Modern video games pose significant challenges for traditional automated testing algorithms, yet intensive testing is crucial to ensure game quality. To address these challenges, researchers designed gaming agents using Reinforcement…

软件工程 · 计算机科学 2026-02-23 Yifei Chen , Sarra Habchi , Lili Wei

Chat-based cybercrime has emerged as a pervasive threat, with attackers leveraging real-time messaging platforms to conduct scams that rely on trust-building, deception, and psychological manipulation. Traditional defense mechanisms, which…

密码学与安全 · 计算机科学 2025-12-29 Yifan Yao , Baojuan Wang , Jinhao Duan , Kaidi Xu , ChuanKai Guo , Zhibo Eric Sun , Yue Zhang

Despite their advanced reasoning capabilities, state-of-the-art Multimodal Large Language Models (MLLMs) demonstrably lack a core component of human intelligence: the ability to `read the room' and assess deception in complex social…

计算机视觉与模式识别 · 计算机科学 2025-11-21 Caixin Kang , Yifei Huang , Liangyang Ouyang , Mingfang Zhang , Ruicong Liu , Yoichi Sato

We present Large Language Model for Mixed Reality (LLMR), a framework for the real-time creation and modification of interactive Mixed Reality experiences using LLMs. LLMR leverages novel strategies to tackle difficult cases where ideal…

Role-playing Large language models (LLMs) are increasingly deployed in high-stakes domains such as healthcare, education, and governance, where failures can directly impact user trust and well-being. A cost effective paradigm for LLM…

计算与语言 · 计算机科学 2025-09-16 Timothy Rupprecht , Enfu Nan , Arash Akbari , Arman Akbari , Lei Lu , Priyanka Maan , Sean Duffy , Pu Zhao , Yumei He , David Kaeli , Yanzhi Wang

Recent advancements in Multimodal Large Language Models (MLLMs) have demonstrated impressive capabilities in visual-text processing. However, existing static image-text benchmarks are insufficient for evaluating their dynamic perception and…

计算机视觉与模式识别 · 计算机科学 2026-04-27 Xiangxi Zheng , Linjie Li , Zhengyuan Yang , Ping Yu , Alex Jinpeng Wang , Rui Yan , Yuan Yao , Lijuan Wang