Centerline Depth World Reinforcement Learning-based Left Atrial Appendage Orifice Localization
专题命中 工具调用 :agent(abstract);planning(abstract);分类 cs.AI
Comments 10 pages, 6 figures
AI 大模型
智能体、工具调用、规划、工作流、多智能体和自主任务执行。
专题命中 工具调用 :agent(abstract);planning(abstract);分类 cs.AI
Comments 10 pages, 6 figures
专题命中 工具调用 :agent(abstract);planning(abstract);分类 cs.AI
Comments 7 pages, 2 figures
专题命中 工具调用 :agent(abstract);multi-agent(abstract);分类 cs.LG
专题命中 工具调用 :agent(abstract);multi-agent(abstract);分类 cs.LG
Comments This paper has been published at ICML2020. This new version made a correction to Proposition 19, and added more related works
专题命中 工具调用 :agent(abstract);planning(abstract);分类 cs.LG
Comments Accepted paper in MIDL 2020
Journal ref https://openreview.net/forum?id=0vDeD2UD0S&referrer=%5BAuthor%20Console%5D(%2Fgroup%3Fid%3DMIDL.io%2F2020%2FConference%2FAuthors%23your-submissions)
专题命中 工具调用 :agent(abstract);multi-agent(abstract);分类 cs.LG
专题命中 工具调用 :agent(abstract);multi-agent(abstract);分类 cs.LG
Comments This paper has been submitted in the 21st IEEE International Workshop On Signal Processing Advances In Wireless Communications (SPAWC 2020)
专题命中 工具调用 :agent(abstract);planning(abstract);分类 cs.LG
Comments 8 pages, 6 figures, Accepted to IROS 2019
专题命中 工具调用 :agent(abstract);planning(abstract);分类 cs.LG
Comments Published at NeurIPS 2019, 17 pages, 3 figures
Journal ref year: 2019; page range: 7214--7223
专题命中 工具调用 :agent(abstract);planning(abstract);分类 cs.LG
Comments Published as a conference paper at ICLR 2020
专题命中 工具调用 :agent(abstract);multi-agent(abstract);分类 cs.AI
Journal ref AAAI 2020
专题命中 工具调用 :agent(abstract);multi-agent(abstract);分类 cs.LG
Comments Submitted to IEEE Wireless Communications Magazine
专题命中 工具调用 :agent(abstract);planning(abstract);分类 cs.AI
Comments The paper needs a major revision including the title
专题命中 工具调用 :agent(abstract);autonomous agent(abstract);分类 cs.AI
Comments CoRL 2018 final version
专题命中 工具调用 :agent(abstract);multi-agent(abstract);分类 cs.AI
专题命中 工具调用 :agent(abstract);multi-agent(abstract);分类 cs.AI
专题命中 工具调用 :agent(abstract);multi-agent(abstract);分类 cs.AI
专题命中 工具调用 :agent(abstract);autonomous agent(abstract);分类 cs.AI
Comments Presented at the Constructive Machine Learning workshop at NIPS 2016 as a poster and spotlight talk. 8 pages including 2 page references, 2 page appendix, 3 figures. Blog post (including videos) at https://medium.com/@memoakten/collaborative-creativity-with-monte-carlo-tree-search-and-convolutional-neural-networks-and-other-69d7107385a0
专题命中 工具调用 :agent(abstract);multi-agent(abstract);分类 cs.AI
专题命中 工具调用 :agent(abstract);multi-agent(abstract);分类 cs.AI
Comments 6 pages, to appear in the proceedings of CICM'2015 conference
专题命中 工具调用 :agent(abstract);multi-agent(abstract);分类 cs.AI
Comments To appear in Theory and Practice of Logic Programming (TPLP)
专题命中 工具调用 :agent(abstract);multi-agent(abstract);分类 cs.AI
Journal ref Journal Of Artificial Intelligence Research, Volume 47, pages 613-647, 2013
专题命中 工具调用 :agent(abstract);planning(abstract);分类 cs.AI
Journal ref Journal Of Artificial Intelligence Research, Volume 39, pages 269-300, 2010
专题命中 工具调用 :agent(abstract);multi-agent(abstract);分类 cs.AI
Comments Extended version of the JELIA 2012 paper with the same title
专题命中 工具调用 :agent(abstract);planning(abstract);分类 cs.AI
Journal ref Journal Of Artificial Intelligence Research, Volume 25, pages 119-157, 2006
专题命中 工具调用 :agent(abstract);multi-agent(abstract);分类 cs.AI
Journal ref Journal Of Artificial Intelligence Research, Volume 28, pages 393-429, 2007
专题命中 工具调用 :agent(abstract);multi-agent(abstract);分类 cs.AI
Comments 12 pages, Submitted to an International Conference
专题命中 工具调用 :agent(abstract);multi-agent(abstract);分类 cs.AI
Comments 6 pages. in: roc. of the Third International Conference on Computational Intelligence, Robotics and Autonomous Systems (CIRAS '05). To appear
EcoAgent-Bench:评估预算约束下大语言模型智能体的经济决策能力
专题命中 工具调用 :agent(abstract,comments);分类 cs.AI、cs.CL、cs.LG
AI总结 本文提出EcoAgent-Bench基准,评估大语言模型智能体在预算约束下的经济决策能力,发现现有智能体在该任务上表现不佳,发布了相关研究资源。
Comments 8 pages, 3 figures, 4 tables. Benchmark, dataset (304 budget-conditioned agent tasks), and evaluation harness; artifacts to be released
PATE-Forensics:以通用多模态大语言模型(MLLM)为工具的可解释深度伪造取证方法
机构 * Harbin Institute of Technology(哈尔滨工业大学)
专题命中 工具调用 :agent(abstract);tool use(abstract)
AI总结 本研究提出PATE-Forensics,采用“感知即工具”范式,基于DINOv3构建取证感知工具,结合通用MLLM实现可解释深度伪造取证,在DDL-X Track 3数据集上取得0.89的最佳官方分数,较次席高出0.19分。
Comments 9 pages, 3 figures, 2 tables; DDL-X Track 3, IJCAI 2026 AI Safety Workshop