Customising General Large Language Models for Specialised Emotion Recognition Tasks
专题命中 指令微调 :large language model(title,abstract);language model(title,abstract);LLM(abstract);分类 cs.CL
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 指令微调 :large language model(title,abstract);language model(title,abstract);LLM(abstract);分类 cs.CL
专题命中 指令微调 :large language model(title,abstract);language model(title,abstract);instruction tuning(abstract);分类 cs.CL
Comments EMNLP2023
专题命中 指令微调 :large language model(title,abstract);language model(title,abstract);LLM(abstract);分类 cs.CL
Comments 5 pages
专题命中 指令微调 :large language model(title,abstract);language model(title,abstract);LLM(abstract);分类 cs.LG
Comments 18 pages
专题命中 指令微调 :large language model(title,abstract);language model(title,abstract);prompting(abstract);分类 cs.CL
Comments Accepted to EMNLP 2023
专题命中 指令微调 :large language model(title,abstract);language model(title,abstract);LLM(abstract);分类 cs.CL
专题命中 指令微调 :large language model(title,abstract);language model(title,abstract);LLM(abstract);分类 cs.LG
专题命中 指令微调 :foundation model(title,abstract);SLM(title,abstract);language model(abstract);分类 cs.CL
专题命中 指令微调 :large language model(title,abstract);language model(title,abstract);prompting(abstract);分类 cs.CL
专题命中 指令微调 :large language model(title,abstract);language model(title,abstract);LLM(abstract);分类 cs.LG
专题命中 指令微调 :large language model(title,abstract);language model(title,abstract);LLM(abstract);分类 cs.CL
Comments 8 pages, 3 tables
专题命中 指令微调 :large language model(title,abstract);language model(title,abstract);instruction tuning(abstract);分类 cs.CL
专题命中 指令微调 :language model(title,abstract);large language model(title);foundation model(abstract);pretraining(abstract)
Comments 10 pages, 4 figures, submitted to ICLR 2023
专题命中 指令微调 :large language model(title,abstract);language model(title,abstract);LLM(abstract);分类 cs.CL
专题命中 指令微调 :large language model(title,abstract);language model(title,abstract);LLM(abstract);分类 cs.CL
专题命中 指令微调 :large language model(title,abstract);language model(title,abstract);LLM(abstract);分类 cs.CL
专题命中 指令微调 :language model(title,abstract);instruction tuning(title,abstract);pretraining(abstract);分类 cs.LG
Comments preprint
专题命中 指令微调 :language model(title,abstract);prompting(title,abstract);large language model(abstract);分类 cs.CL
专题命中 指令微调 :large language model(title,abstract);language model(title,abstract);prompting(abstract);分类 cs.CL
专题命中 指令微调 :large language model(title,abstract);language model(title,abstract);instruction tuning(abstract);分类 cs.CL
Comments 10 pages, 9 figures, accepted by Findings of ACL2023
专题命中 指令微调 :large language model(title,abstract);language model(title,abstract);LLM(abstract);分类 cs.CL
Comments ACL 2023 Findings; The code is available at https://github.com/OSU-NLP-Group/QA4RE
专题命中 指令微调 :large language model(title,abstract);language model(title,abstract);LLM(abstract);分类 cs.CL
专题命中 指令微调 :large language model(title,abstract);language model(title,abstract);LLM(abstract);分类 cs.CL
Comments Publised at IEEE ICDM Workshop on Machine Learning for Cybersecurity (MLC) 2022
Journal ref 2022 IEEE International Conference on Data Mining Workshops (ICDMW), pp. 560-566
专题命中 指令微调 :large language model(title,abstract);language model(title,abstract);instruction tuning(abstract);分类 cs.CL
专题命中 指令微调 :large language model(title,abstract);language model(title,abstract);LLM(abstract);分类 cs.LG
Comments Accepted in DATE 2023. 7 pages, 4 tables, 7 figures
专题命中 指令微调 :large language model(title,abstract);language model(title,abstract);LLM(abstract);分类 cs.CL
Comments 15 pages, 7 figures, 8 tables. Accepted as a long paper at NAACL 2022
专题命中 指令微调 :large language model(title,abstract);language model(title,abstract);prompting(abstract);分类 cs.CL
专题命中 指令微调 :LLM(title,abstract);language model(title,abstract);large language model(abstract)
Comments LLM-wrapper (v3) is published as a conference paper at ICLR 2025. (v1 was presented at EVAL-FoMo workshop, ECCV 2024.)
基于美国核管理委员会反应堆操作员执照考试的多模态语言模型微调与检索策略基准测试
机构 * organization= Department of Nuclear Engineering, Hanyang University , addressline= 222 Wangsimni-ro , postcode= 04763 , state= Seongdong-gu , city= Seoul , country= South Korea ; organization= The Grainger College of Engineering, Nuclear, Plasma \& Radiological Engineering, University of Illinois Urbana-Champaign , city= Urbana , state= IL , country= USA
专题命中 指令微调 :SFT(summary_cn,abstract);language model(title,abstract);分类 cs.CL、cs.AI
AI总结 该研究针对美国核管理委员会反应堆操作员执照考试,评估310亿参数多模态模型应用核知识的能力,通过对比基础模型与多种微调及检索配置,发现固定大小分块RAG的SFT配置表现最佳,并揭示了分块策略规律及RAFT与SFT的性能差异。
当API“说错”语言:重新审视多语言工具使用的后训练
机构 * Amazon(亚马逊)
专题命中 指令微调 :post-training(title,abstract);SFT(abstract,abstract_cn);large language model(abstract);language model(abstract)
AI总结 针对多语言API调用中存在的参数语言不匹配问题,研究发现监督微调可实现接近或优于复杂强化学习方法的性能,强化学习仅能提供渐进式改进。