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Creative thinking is a fundamental aspect of human cognition, and divergent thinking-the capacity to generate novel and varied ideas-is widely regarded as its core generative engine. Large language models (LLMs) have recently demonstrated…

Large Language Models (LLMs) have transformed the Natural Language Processing (NLP) landscape with their remarkable ability to understand and generate human-like text. However, these models are prone to ``hallucinations'' -- outputs that do…

The escalating global mental health crisis, marked by persistent treatment gaps, availability, and a shortage of qualified therapists, positions Large Language Models (LLMs) as a promising avenue for scalable support. While LLMs offer…

While brain-aligned large language models (LLMs) have garnered attention for their potential as cognitive models and for potential for enhanced safety and trustworthiness in AI, the role of this brain alignment for linguistic competence…

计算与语言 · 计算机科学 2026-03-25 Gabriele Merlin , Mariya Toneva

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…

计算与语言 · 计算机科学 2026-05-19 Hoyun Song , Migyeong Kang , Jisu Shin , Jihyun Kim , Chanbi Park , Hangyeol Yoo , Jihyun An , Alice Oh , Jinyoung Han , KyungTae Lim

Creating controlled methods to simulate neurodegeneration in artificial intelligence (AI) is crucial for applications that emulate brain function decline and cognitive disorders. We use IQ tests performed by Large Language Models (LLMs)…

计算与语言 · 计算机科学 2024-03-19 Antonios Alexos , Yu-Dai Tsai , Ian Domingo , Maryam Pishgar , Pierre Baldi

Conventional mechanical design follows an iterative process in which initial concepts are refined through cycles of expert assessment and resource-intensive Finite Element Method (FEM) analysis to meet performance goals. While machine…

机器学习 · 计算机科学 2025-05-02 Yayati Jadhav , Amir Barati Farimani

Large language models (LLMs) often match or exceed clinician-level performance on medical benchmarks, yet very few are evaluated on real clinical data or examined beyond headline metrics. We present, to our knowledge, the first evaluation…

Trained on a vast amount of data, Large Language models (LLMs) have achieved unprecedented success and generalization in modeling fairly complex textual inputs in the abstract space, making them powerful tools for zero-shot learning. Such…

计算机视觉与模式识别 · 计算机科学 2023-05-19 Shervin Ardeshir

Large language models (LLMs) have demonstrated human-like abilities in language-based tasks. While language is a defining feature of human intelligence, it emerges from more fundamental neurophysical processes rather than constituting the…

神经元与认知 · 定量生物学 2025-09-12 Doai Ngo , Mingxuan Sun , Zhengji Zhang , Ashwin G Ramayya , Mark Schnitzer , Zhe Zhao

Large language models (LLMs) achieve strong average performance yet remain unreliable at the instance level, with frequent hallucinations, brittle failures, and poorly calibrated confidence. We study reliability through the lens of…

人工智能 · 计算机科学 2026-01-13 Pranav Kallem

Large Language Models (LLMs) are powerful linguistic engines but remain susceptible to hallucinations: plausible-sounding outputs that are factually incorrect or unsupported. In this work, we present a mathematically grounded framework to…

计算与语言 · 计算机科学 2025-11-20 Moses Kiprono

Mental disorders are clinically significant patterns of behavior that are associated with stress and/or impairment in social, occupational, or family activities. People suffering from such disorders are often misjudged and poorly diagnosed…

机器学习 · 计算机科学 2025-09-03 Abu Shad Ahammed , Sayeri Mukherjee , Roman Obermaisser

Large Language Models (LLMs) have demonstrated remarkable capabilities in reasoning and generation, serving as the foundation for advanced persona simulation and Role-Playing Language Agents (RPLAs). However, achieving authentic alignment…

计算与语言 · 计算机科学 2026-04-20 Xintao Wang , Jian Yang , Weiyuan Li , Rui Xie , Jen-tse Huang , Jun Gao , Shuai Huang , Yueping Kang , Yuanli Gou , Hongwei Feng , Yanghua Xiao

Despite the rapid expansion of Large Language Models (LLMs) in healthcare, robust and explainable evaluation of their ability to assess clinical trial reporting according to CONSORT standards remains an open challenge. In particular,…

人工智能 · 计算机科学 2026-02-26 Sohyeon Jeon , Hyung-Chul Lee

Vision-Language Models (VLMs) frequently "hallucinate" - generate plausible yet factually incorrect statements - posing a critical barrier to their trustworthy deployment. In this work, we propose a new paradigm for diagnosing…

计算机视觉与模式识别 · 计算机科学 2026-03-17 Lexiang Xiong , Qi Li , Jingwen Ye , Xinchao Wang

Multimodal large language models (MLLMs) demonstrate considerable potential in clinical diagnostics, a domain that inherently requires synthesizing complex visual and textual data alongside consulting authoritative medical literature.…

计算与语言 · 计算机科学 2026-03-23 Yannian Gu , Zhongzhen Huang , Linjie Mu , Xizhuo Zhang , Shaoting Zhang , Xiaofan Zhang

Large Language Models (LLMs) have become foundational tools in natural language processing, powering a wide range of applications and research. Many studies have shown that LLMs share significant similarities with the human brain. Recent…

人工智能 · 计算机科学 2026-02-10 Zixuan Qin , Qingchen Yu , Kunlin Lyu , Zhaoxin Fan , Yifan Sun

The deployment of large language models (LLMs) as interactive agents has exposed a category of behavioral failure that prevailing terminology, principally hallucination, fails to adequately characterize. This paper introduces LLM Psychosis…

计算机与社会 · 计算机科学 2026-04-30 Ashutosh Raj