Network Traffic Anomaly Detection Using Recurrent Neural Networks
专题命中 长上下文与记忆 :language model(abstract);分类 cs.LG
Comments Prepared for the 2017 National Symposium on Sensor and Data Fusion
AI 大模型
大语言模型、预训练、指令微调、后训练和语言模型应用。
专题命中 长上下文与记忆 :language model(abstract);分类 cs.LG
Comments Prepared for the 2017 National Symposium on Sensor and Data Fusion
专题命中 长上下文与记忆 :language model(abstract);分类 cs.LG
Comments Submitted for Interspeech 2018
专题命中 长上下文与记忆 :language model(abstract);分类 cs.LG
专题命中 长上下文与记忆 :language model(abstract);分类 cs.CL
专题命中 长上下文与记忆 :language model(abstract);分类 cs.CL
Comments Accepted in JNLE Special Issue: Language for Images (24.3) (expanded with content that was removed from journal paper in order to reduce number of pages), 28 pages, 5 figures, 6 tables
专题命中 长上下文与记忆 :language model(abstract);分类 cs.LG
Comments Published as a conference paper at ICLR 2018
专题命中 长上下文与记忆 :language model(abstract);分类 cs.CL
专题命中 长上下文与记忆 :language model(abstract);分类 cs.CL
Comments Accepted to 2018 IEEE International Conference on Acoustics, Speech and Signal Processing
专题命中 长上下文与记忆 :language model(abstract);分类 cs.CL
Comments 21 pages, 11 figures
专题命中 长上下文与记忆 :language model(abstract);分类 cs.CL
Comments 8 pages, 3 figures, In Proceedings of AAAI 2018
专题命中 长上下文与记忆 :language model(abstract);分类 cs.CL
Comments 6 pages
专题命中 长上下文与记忆 :language model(abstract);分类 cs.LG
专题命中 长上下文与记忆 :language model(abstract);分类 cs.CL
Comments 5 pages, 3 figures, EMNLP 2017 submitted
专题命中 长上下文与记忆 :language model(abstract);分类 cs.CL
Comments 15 pages; to appear in Transactions of the Association for Computational Linguistics
专题命中 长上下文与记忆 :language model(abstract);分类 cs.LG
Comments in 30th Conference on Neural Information Processing Systems (NIPS 2016), Barcelona, Spain
专题命中 长上下文与记忆 :language model(abstract);分类 cs.CL
Comments EMNLP 2016
专题命中 长上下文与记忆 :language model(abstract);分类 cs.CL
Comments Published as a conference paper at EMNLP 2016
专题命中 长上下文与记忆 :language model(abstract);分类 cs.CL
Comments Submitted to Interspeech 2016
专题命中 长上下文与记忆 :language model(abstract);分类 cs.CL
专题命中 长上下文与记忆 :language model(abstract);分类 cs.CL
Comments 5 pages
专题命中 长上下文与记忆 :language model(abstract);分类 cs.AI
Comments 9 pages
专题命中 长上下文与记忆 :language model(abstract);分类 cs.CL
专题命中 长上下文与记忆 :language model(abstract);分类 cs.CL
Comments Accepted to NIPS 2015
专题命中 长上下文与记忆 :language model(abstract);分类 cs.CL
Comments 5 pages, 1 figure
专题命中 长上下文与记忆 :language model(abstract);分类 cs.CL
Comments Content presented in 2015 Jelinek Summer Workshop on Speech and Language Technology on August 14th 2015
专题命中 长上下文与记忆 :language model(abstract);分类 cs.CL
Comments Published in INTERSPEECH 2015, Dresden, Germany
专题命中 长上下文与记忆 :language model(abstract);分类 cs.LG
Comments 9 pages, removed appendix
专题命中 长上下文与记忆 :language model(abstract);分类 cs.LG
专题命中 长上下文与记忆 :language model(abstract);分类 cs.CL
Comments 8 pages, uses aclap.sty, To appear in Proc. ACL/EACL 97
BIT-Nav: 具身导航的脑启发轨迹记忆
机构 * Johns Hopkins University(约翰霍普金斯大学) ; DEVCOM Army Research Laboratory(DEVCOM陆军研究实验室)
专题命中 长上下文与记忆 :language model(abstract);LLM(comments)
AI总结 提出BIT-Nav框架,通过轻量级学习轨迹记忆增强冻结的视觉-语言模型导航,解决长序列中帧采样稀疏问题,以恒定token成本编码结构化运动历史。
Comments Accepted to CVPR 2026: 2nd Workshop on 3D-LLM/VLA: Bridging Language, Vision and Action in 3D Environments