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The ability to plan a course of action that achieves a desired state of affairs has long been considered a core competence of intelligent agents and has been an integral part of AI research since its inception. With the advent of large…

人工智能 · 计算机科学 2024-09-23 Karthik Valmeekam , Kaya Stechly , Subbarao Kambhampati

Recent advancements in Large Language Models (LLMs) have showcased their ability to perform complex reasoning tasks, but their effectiveness in planning remains underexplored. In this study, we evaluate the planning capabilities of OpenAI's…

人工智能 · 计算机科学 2024-10-15 Kevin Wang , Junbo Li , Neel P. Bhatt , Yihan Xi , Qiang Liu , Ufuk Topcu , Zhangyang Wang

Enabling Large Language Models (LLMs) to handle a wider range of complex tasks (e.g., coding, math) has drawn great attention from many researchers. As LLMs continue to evolve, merely increasing the number of model parameters yields…

Language has long been conceived as an essential tool for human reasoning. The breakthrough of Large Language Models (LLMs) has sparked significant research interest in leveraging these models to tackle complex reasoning tasks. Researchers…

We examine the reasoning and planning capabilities of large language models (LLMs) in solving complex tasks. Recent advances in inference-time techniques demonstrate the potential to enhance LLM reasoning without additional training by…

人工智能 · 计算机科学 2025-02-19 Shubham Parashar , Blake Olson , Sambhav Khurana , Eric Li , Hongyi Ling , James Caverlee , Shuiwang Ji

Large language models (LLMs) have exhibited remarkable capabilities across various domains and tasks, pushing the boundaries of our knowledge in learning and cognition. The latest model, OpenAI's o1, stands out as the first LLM with an…

计算与语言 · 计算机科学 2024-09-24 Yunfei Xie , Juncheng Wu , Haoqin Tu , Siwei Yang , Bingchen Zhao , Yongshuo Zong , Qiao Jin , Cihang Xie , Yuyin Zhou

Reasoning language models (RLMs), also known as Large Reasoning Models (LRMs), such as OpenAI's o1 and o3, DeepSeek-R1, and Alibaba's QwQ, have redefined AI's problem-solving capabilities by extending LLMs with advanced reasoning…

The planning ability of Large Language Models (LLMs) has garnered increasing attention in recent years due to their remarkable capacity for multi-step reasoning and their ability to generalize across a wide range of domains. While some…

人工智能 · 计算机科学 2025-02-19 Mohamed Aghzal , Erion Plaku , Gregory J. Stein , Ziyu Yao

Recent developments, particularly OpenAI's O1 model, have demonstrated the remarkable potential of Large Language Models (LLMs) for complex reasoning tasks. Through analysis of O1's outputs and provided sample Chain-of-Thought (CoT)…

人工智能 · 计算机科学 2024-12-09 Toby Simonds , Jey Han Lau , Chaithanya Bandi

Planning for an upcoming project iteration (sprint) is one of the key activities in Scrum planning. In this paper, we present our work in progress on exploring the applicability of Large Language Models (LLMs) for solving this problem. We…

软件工程 · 计算机科学 2025-12-23 Yuwon Yoon , Kevin Iwan , Madeleine Zwart , Xiaohan Qin , Hina Lee , Maria Spichkova

With the emergence of advanced reasoning models like OpenAI o3 and DeepSeek-R1, large language models (LLMs) have demonstrated remarkable reasoning capabilities. However, their ability to perform rigorous logical reasoning remains an open…

人工智能 · 计算机科学 2025-02-14 Hanmeng Liu , Zhizhang Fu , Mengru Ding , Ruoxi Ning , Chaoli Zhang , Xiaozhang Liu , Yue Zhang

The performance of large language models (LLMs) has recently improved to the point where models can perform well on many language tasks. We show here that--for the first time--the models can also generate valid metalinguistic analyses of…

计算与语言 · 计算机科学 2025-07-14 Gašper Beguš , Maksymilian Dąbkowski , Ryan Rhodes

Recently, test-time scaling has garnered significant attention from the research community, largely due to the substantial advancements of the o1 model released by OpenAI. By allocating more computational resources during the inference…

In "Embers of Autoregression" (McCoy et al., 2023), we showed that several large language models (LLMs) have some important limitations that are attributable to their origins in next-word prediction. Here we investigate whether these issues…

计算与语言 · 计算机科学 2024-10-07 R. Thomas McCoy , Shunyu Yao , Dan Friedman , Mathew D. Hardy , Thomas L. Griffiths

Large Reasoning Models (LRMs) such as DeepSeek-R1 and OpenAI o1 have demonstrated remarkable capabilities in various reasoning tasks. Their strong capability to generate and reason over intermediate thoughts has also led to arguments that…

计算与语言 · 计算机科学 2025-10-17 Saurabh Srivastava , Ziyu Yao

Recent advancements in Large Reasoning Models (LRMs), such as OpenAI's o1/o3 and DeepSeek-R1, have demonstrated remarkable performance in specialized reasoning tasks through human-like deliberative thinking and long chain-of-thought…

人工智能 · 计算机科学 2025-11-20 Weixiang Zhao , Xingyu Sui , Jiahe Guo , Yulin Hu , Yang Deng , Yanyan Zhao , Xuda Zhi , Yongbo Huang , Hao He , Wanxiang Che , Ting Liu , Bing Qin

Large reasoning models (LRMs) like OpenAI-o1 have demonstrated impressive long stepwise reasoning capabilities through large-scale reinforcement learning. However, their extended reasoning processes often suffer from knowledge…

人工智能 · 计算机科学 2025-01-10 Xiaoxi Li , Guanting Dong , Jiajie Jin , Yuyao Zhang , Yujia Zhou , Yutao Zhu , Peitian Zhang , Zhicheng Dou

Large language models (LLMs) have demonstrated significant potential to accelerate scientific discovery as valuable tools for analyzing data, generating hypotheses, and supporting innovative approaches in various scientific fields. In this…

计算与语言 · 计算机科学 2025-10-30 Jin Huang , Silviu Cucerzan , Sujay Kumar Jauhar , Ryen W. White

Recent Large Reasoning Models (LRMs), such as DeepSeek-R1 and OpenAI o1, have demonstrated strong performance gains by scaling up the length of Chain-of-Thought (CoT) reasoning during inference. However, a growing concern lies in their…

The growing power of large language models (LLMs) has revolutionized how people access and utilize information. Notably, the LLMs excel at performing fine-grained data representation, which facilitates precise retrieval of information. They…

计算与语言 · 计算机科学 2025-02-13 Ruiran Yan , Zheng Liu , Defu Lian
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