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相关论文: LLM Jaggedness Unlocks Scientific Creativity

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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…

计算与语言 · 计算机科学 2024-08-07 Philipp Mondorf , Barbara Plank

Large language models (LLMs) are increasingly used to support creative tasks such as research idea generation. While recent work has shown that structured dialogues between LLMs can improve the novelty and feasibility of generated ideas,…

计算与语言 · 计算机科学 2025-07-14 Keisuke Ueda , Wataru Hirota , Takuto Asakura , Takahiro Omi , Kosuke Takahashi , Kosuke Arima , Tatsuya Ishigaki

With the release of ChatGPT and other large language models (LLMs) the discussion about the intelligence, possibilities, and risks, of current and future models have seen large attention. This discussion included much debated scenarios…

人工智能 · 计算机科学 2024-07-31 Nils Körber , Silvan Wehrli , Christopher Irrgang

Cognitive dynamics are pivotal to advance human understanding of the world. Recent advancements in large language models (LLMs) reveal their potential for cognitive simulation. However, these LLM-based cognitive studies primarily focus on…

计算与语言 · 计算机科学 2024-09-25 Yaojia Lv , Haojie Pan , Zekun Wang , Jiafeng Liang , Yuanxing Liu , Ruiji Fu , Ming Liu , Zhongyuan Wang , Bing Qin

Recently developed large language models (LLMs) have been shown to perform remarkably well on a wide range of language understanding tasks. But, can they really "reason" over the natural language? This question has been receiving…

计算与语言 · 计算机科学 2024-06-07 Mihir Parmar , Nisarg Patel , Neeraj Varshney , Mutsumi Nakamura , Man Luo , Santosh Mashetty , Arindam Mitra , Chitta Baral

Despite the dramatic progress in Large Language Model (LLM) development, LLMs often provide seemingly plausible but not factual information, often referred to as hallucinations. Retrieval-augmented LLMs provide a non-parametric approach to…

计算与语言 · 计算机科学 2023-11-09 Sai Munikoti , Anurag Acharya , Sridevi Wagle , Sameera Horawalavithana

In the rapidly evolving field of Large Language Models (LLMs), there is a critical need to thoroughly analyze their capabilities and risks. Central to our investigation are two novel elements. Firstly, it is the innovative parallels between…

人工智能 · 计算机科学 2024-03-07 Jianqiiu Zhang

Large language models (LLMs) have been touted to enable increased productivity in many areas of today's work life. Scientific research as an area of work is no exception: the potential of LLM-based tools to assist in the daily work of…

软件工程 · 计算机科学 2024-04-24 Mohamed Nejjar , Luca Zacharias , Fabian Stiehle , Ingo Weber

Large Multimodal Models (LMMs) have achieved remarkable progress across various capabilities; however, complex video reasoning in the scientific domain remains a significant and challenging frontier. Current video benchmarks predominantly…

计算机视觉与模式识别 · 计算机科学 2025-10-10 Andong Deng , Taojiannan Yang , Shoubin Yu , Lincoln Spencer , Mohit Bansal , Chen Chen , Serena Yeung-Levy , Xiaohan Wang

In the field of Artificial (General) Intelligence (AI), the several recent advancements in Natural language processing (NLP) activities relying on Large Language Models (LLMs) have come to encourage the adoption of LLMs as scientific models…

计算与语言 · 计算机科学 2023-10-18 Evelina Leivada , Vittoria Dentella , Elliot Murphy

Human-defined creativity is highly abstract, posing a challenge for multimodal large language models (MLLMs) to comprehend and assess creativity that aligns with human judgments. The absence of an existing benchmark further exacerbates this…

Large language models (LLMs), particularly when integrated into agentic systems, have demonstrated human- and even superhuman-level performance across multiple domains. Whether these systems can truly be considered creative, however,…

计算机与社会 · 计算机科学 2026-04-21 Giorgio Franceschelli , Mirco Musolesi

Advances in large language models (LLMs) are rapidly transforming scientific work, yet empirical evidence on how these systems reshape research activities remains limited. We report a mixed-methods pilot evaluation of an AI-orchestrated…

计算机与社会 · 计算机科学 2026-02-24 Yuan An

Large language models (LLMs) have shown strong performance on mathematical reasoning under well-defined conditions. However, real-world engineering problems involve uncertainty, context, and open-ended settings that extend beyond symbolic…

人工智能 · 计算机科学 2026-05-05 Xiyuan Zhou , Xinlei Wang , Yirui He , Yang Wu , Ruixi Zou , Yuheng Cheng , Yulu Xie , Wenxuan Liu , Huan Zhao , Yan Xu , Jinjin Gu , Junhua Zhao

In the rapidly evolving domain of Natural Language Generation (NLG) evaluation, introducing Large Language Models (LLMs) has opened new avenues for assessing generated content quality, e.g., coherence, creativity, and context relevance.…

计算与语言 · 计算机科学 2024-06-13 Zhen Li , Xiaohan Xu , Tao Shen , Can Xu , Jia-Chen Gu , Yuxuan Lai , Chongyang Tao , Shuai Ma

Large Language Models (LLMs) have shown remarkable capabilities in manipulating natural language across multiple applications, but their ability to handle simple reasoning tasks is often questioned. In this work, we aim to provide a…

计算与语言 · 计算机科学 2025-05-05 Alessandro Raganato , Rafael Peñaloza , Marco Viviani , Gabriella Pasi

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…

计算与语言 · 计算机科学 2026-02-26 Qiran Zou , Hou Hei Lam , Wenhao Zhao , Yiming Tang , Tingting Chen , Samson Yu , Tianyi Zhang , Chang Liu , Xiangyang Ji , Dianbo Liu

Strong Artificial Intelligence (Strong AI) or Artificial General Intelligence (AGI) with abstract reasoning ability is the goal of next-generation AI. Recent advancements in Large Language Models (LLMs), along with the emerging field of…

计算与语言 · 计算机科学 2024-01-19 Yiqi Wang , Wentao Chen , Xiaotian Han , Xudong Lin , Haiteng Zhao , Yongfei Liu , Bohan Zhai , Jianbo Yuan , Quanzeng You , Hongxia Yang

Large language models (LLMs) have demonstrated their remarkable performance across various language understanding tasks. While emerging benchmarks have been proposed to evaluate LLMs in various domains such as mathematics and computer…

人工智能 · 计算机科学 2024-10-28 Junnan Dong , Zijin Hong , Yuanchen Bei , Feiran Huang , Xinrun Wang , Xiao Huang

Large language models (LLMs) have emerged as powerful tools for many AI problems and exhibit remarkable in-context learning (ICL) capabilities. Compositional ability, solving unseen complex tasks that combine two or more simple tasks, is an…

计算与语言 · 计算机科学 2024-08-13 Zhuoyan Xu , Zhenmei Shi , Yingyu Liang