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相关论文: o3-mini vs DeepSeek-R1: Which One is Safer?

200 篇论文

DeepSeek recently released R1, a high-performing large language model (LLM) optimized for reasoning tasks. Despite its efficient training pipeline, R1 achieves competitive performance, even surpassing leading reasoning models like OpenAI's…

计算与语言 · 计算机科学 2025-05-20 Ali Naseh , Harsh Chaudhari , Jaechul Roh , Mingshi Wu , Alina Oprea , Amir Houmansadr

This study evaluates the ability of DeepSeek, an open-source large language model (LLM), to simulate public opinions in comparison to LLMs developed by major tech companies. By comparing DeepSeek-R1 and DeepSeek-V3 with Qwen2.5, GPT-4o, and…

计算与语言 · 计算机科学 2025-09-16 Weihong Qi , Fan Huang , Jisun An , Haewoon Kwak

This paper introduces fourteen novel datasets for the evaluation of Large Language Models' safety in the context of enterprise tasks. A method was devised to evaluate a model's safety, as determined by its ability to follow instructions and…

计算与语言 · 计算机科学 2024-04-16 David Nadeau , Mike Kroutikov , Karen McNeil , Simon Baribeau

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

As large language models (LLMs) move from research prototypes to enterprise systems, their security vulnerabilities pose serious risks to data privacy and system integrity. This study benchmarks various Llama model variants against the…

密码学与安全 · 计算机科学 2026-01-29 Nourin Shahin , Izzat Alsmadi

Background: AI-powered code generation, fueled by Large Language Models (LLMs), is revolutionizing software development. Models like OpenAI's Codex and GPT-4, alongside DeepSeek, leverage vast code and natural language datasets. However,…

软件工程 · 计算机科学 2025-02-27 Md Motaleb Hossen Manik

DeepSeek, a Chinese Artificial Intelligence (AI) startup, has released their V3 and R1 series models, which attracted global attention due to their low cost, high performance, and open-source advantages. This paper begins by reviewing the…

人工智能 · 计算机科学 2025-07-15 Luolin Xiong , Haofen Wang , Xi Chen , Lu Sheng , Yun Xiong , Jingping Liu , Yanghua Xiao , Huajun Chen , Qing-Long Han , Yang Tang

Large Language Models (LLMs) have shown impressive performance on a range of educational tasks, but are still understudied for their potential to solve mathematical problems. In this study, we compare three prominent LLMs, including GPT-4o,…

人工智能 · 计算机科学 2025-07-01 Ruonan Wang , Runxi Wang , Yunwen Shen , Chengfeng Wu , Qinglin Zhou , Rohitash Chandra

Large Language Models (LLMs) have recently gained attention due to their ability to understand and generate sophisticated human-like content. However, ensuring their safety is paramount as they might provide harmful and unsafe responses.…

软件工程 · 计算机科学 2025-01-29 Miriam Ugarte , Pablo Valle , José Antonio Parejo , Sergio Segura , Aitor Arrieta

We introduce Open Deep Search (ODS) to close the increasing gap between the proprietary search AI solutions, such as Perplexity's Sonar Reasoning Pro and OpenAI's GPT-4o Search Preview, and their open-source counterparts. The main…

Recent incidents highlight safety risks in Large Language Models (LLMs), motivating research into alignment methods like Constitutional AI (CAI). This paper explores CAI's self-critique mechanism on small, uncensored 7-9B parameter models:…

机器学习 · 计算机科学 2025-04-14 Antonio-Gabriel Chacón Menke , Phan Xuan Tan

As Large Language Models (LLMs) increasingly power applications used by children and adolescents, ensuring safe and age-appropriate interactions has become an urgent ethical imperative. Despite progress in AI safety, current evaluations…

计算机与社会 · 计算机科学 2026-05-26 Junfeng Jiao , Saleh Afroogh , Kevin Chen , Abhejay Murali , David Atkinson , Amit Dhurandhar

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…

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

As AI systems become more advanced, concerns about large-scale risks from misuse or accidents have grown. This report analyzes the technical research into safe AI development being conducted by three leading AI companies: Anthropic, Google…

计算机与社会 · 计算机科学 2024-09-26 Oscar Delaney , Oliver Guest , Zoe Williams

Recently, DeepSeek has been the focus of attention in and beyond the AI community. An interesting problem is how DeepSeek compares to other large language models (LLMs). There are many tasks an LLM can do, and in this paper, we use the task…

计算与语言 · 计算机科学 2025-12-29 Tianchen Gao , Jiashun Jin , Zheng Tracy Ke , Gabriel Moryoussef

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…

Large Reasoning Models (LRMs) have achieved remarkable success on reasoning-intensive tasks such as mathematics and programming. However, their enhanced reasoning capabilities do not necessarily translate to improved safety performance-and…

Large language models (LLMs) offer transformative potential for clinical decision support in spine surgery but pose significant risks through hallucinations, which are factually inconsistent or contextually misaligned outputs that may…

机器学习 · 计算机科学 2025-11-21 Dong Chen , Yanzhe Wei , Zonglin He , Guan-Ming Kuang , Canhua Ye , Meiru An , Huili Peng , Yong Hu , Huiren Tao , Kenneth MC Cheung

Security code review is a time-consuming and labor-intensive process typically requiring integration with automated security defect detection tools. However, existing security analysis tools struggle with poor generalization, high false…

软件工程 · 计算机科学 2026-05-12 Jiaxin Yu , Peng Liang , Yujia Fu , Amjed Tahir , Mojtaba Shahin , Chong Wang , Yangxiao Cai