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Article: A Survey of Reasoning with Foundation Models: Concepts, Methodologies, and Outlook
| Title | A Survey of Reasoning with Foundation Models: Concepts, Methodologies, and Outlook |
|---|---|
| Authors | Sun, JiankaiZheng, ChuanyangXie, EnzeLiu, ZhengyingChu, RuihangQiu, JianingXu, JiaqiDing, MingyuLi, HongyangGeng, MengzheWu, YueWang, WenhaiChen, JunsongYin, ZhangyueRen, XiaozheFu, JieHe, JunxianWu, YuanLiu, QiLiu, XihuiLi, YuDong, HaoCheng, YuZhang, MingHeng, Pheng AnnDai, JifengLuo, PingWang, JingdongWen, Ji RongQiu, XipengGuo, YikeXiong, HuiLiu, QunLi, Zhenguo |
| Keywords | AI agent artificial general intelligence foundation models multimodal Reasoning |
| Issue Date | 12-Jun-2025 |
| Publisher | Association for Computing Machinery (ACM) |
| Citation | ACM Computing Surveys, 2025, v. 57, n. 11 How to Cite? |
| Abstract | Reasoning, a crucial ability for complex problem-solving, plays a pivotal role in various real-world settings such as negotiation, medical diagnosis, and criminal investigation. It serves as a fundamental methodology in the field of Artificial General Intelligence (AGI). With the ongoing development of foundation models, there is a growing interest in exploring their abilities in reasoning tasks. In this article, we introduce seminal foundation models proposed or adaptable for reasoning, highlighting the latest advancements in various reasoning tasks, methods, and benchmarks. We then delve into the potential future directions behind the emergence of reasoning abilities within foundation models. We also discuss the relevance of multimodal learning, autonomous agents, and super alignment in the context of reasoning. By discussing these future research directions, we hope to inspire researchers in their exploration of this field, stimulate further advancements in reasoning with foundation models, e.g., Large Language Models (LLMs), and contribute to the development of AGI. |
| Persistent Identifier | http://hdl.handle.net/10722/359182 |
| ISSN | 2023 Impact Factor: 23.8 2023 SCImago Journal Rankings: 6.280 |
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Sun, Jiankai | - |
| dc.contributor.author | Zheng, Chuanyang | - |
| dc.contributor.author | Xie, Enze | - |
| dc.contributor.author | Liu, Zhengying | - |
| dc.contributor.author | Chu, Ruihang | - |
| dc.contributor.author | Qiu, Jianing | - |
| dc.contributor.author | Xu, Jiaqi | - |
| dc.contributor.author | Ding, Mingyu | - |
| dc.contributor.author | Li, Hongyang | - |
| dc.contributor.author | Geng, Mengzhe | - |
| dc.contributor.author | Wu, Yue | - |
| dc.contributor.author | Wang, Wenhai | - |
| dc.contributor.author | Chen, Junsong | - |
| dc.contributor.author | Yin, Zhangyue | - |
| dc.contributor.author | Ren, Xiaozhe | - |
| dc.contributor.author | Fu, Jie | - |
| dc.contributor.author | He, Junxian | - |
| dc.contributor.author | Wu, Yuan | - |
| dc.contributor.author | Liu, Qi | - |
| dc.contributor.author | Liu, Xihui | - |
| dc.contributor.author | Li, Yu | - |
| dc.contributor.author | Dong, Hao | - |
| dc.contributor.author | Cheng, Yu | - |
| dc.contributor.author | Zhang, Ming | - |
| dc.contributor.author | Heng, Pheng Ann | - |
| dc.contributor.author | Dai, Jifeng | - |
| dc.contributor.author | Luo, Ping | - |
| dc.contributor.author | Wang, Jingdong | - |
| dc.contributor.author | Wen, Ji Rong | - |
| dc.contributor.author | Qiu, Xipeng | - |
| dc.contributor.author | Guo, Yike | - |
| dc.contributor.author | Xiong, Hui | - |
| dc.contributor.author | Liu, Qun | - |
| dc.contributor.author | Li, Zhenguo | - |
| dc.date.accessioned | 2025-08-23T00:30:28Z | - |
| dc.date.available | 2025-08-23T00:30:28Z | - |
| dc.date.issued | 2025-06-12 | - |
| dc.identifier.citation | ACM Computing Surveys, 2025, v. 57, n. 11 | - |
| dc.identifier.issn | 0360-0300 | - |
| dc.identifier.uri | http://hdl.handle.net/10722/359182 | - |
| dc.description.abstract | <p>Reasoning, a crucial ability for complex problem-solving, plays a pivotal role in various real-world settings such as negotiation, medical diagnosis, and criminal investigation. It serves as a fundamental methodology in the field of Artificial General Intelligence (AGI). With the ongoing development of foundation models, there is a growing interest in exploring their abilities in reasoning tasks. In this article, we introduce seminal foundation models proposed or adaptable for reasoning, highlighting the latest advancements in various reasoning tasks, methods, and benchmarks. We then delve into the potential future directions behind the emergence of reasoning abilities within foundation models. We also discuss the relevance of multimodal learning, autonomous agents, and super alignment in the context of reasoning. By discussing these future research directions, we hope to inspire researchers in their exploration of this field, stimulate further advancements in reasoning with foundation models, e.g., Large Language Models (LLMs), and contribute to the development of AGI.</p> | - |
| dc.language | eng | - |
| dc.publisher | Association for Computing Machinery (ACM) | - |
| dc.relation.ispartof | ACM Computing Surveys | - |
| dc.subject | AI agent | - |
| dc.subject | artificial general intelligence | - |
| dc.subject | foundation models | - |
| dc.subject | multimodal | - |
| dc.subject | Reasoning | - |
| dc.title | A Survey of Reasoning with Foundation Models: Concepts, Methodologies, and Outlook | - |
| dc.type | Article | - |
| dc.identifier.doi | 10.1145/3729218 | - |
| dc.identifier.scopus | eid_2-s2.0-105011252361 | - |
| dc.identifier.volume | 57 | - |
| dc.identifier.issue | 11 | - |
| dc.identifier.eissn | 1557-7341 | - |
| dc.identifier.issnl | 0360-0300 | - |
