找回密码
 To register

QQ登录

只需一步,快速开始

扫一扫,访问微社区

Titlebook: Analysis of Images, Social Networks and Texts; 11th International C Dmitry I. Ignatov,Michael Khachay,Sergey Zagoruyko Conference proceedin

[复制链接]
楼主: Clientele
发表于 2025-3-28 16:39:41 | 显示全部楼层
发表于 2025-3-28 21:37:53 | 显示全部楼层
发表于 2025-3-29 00:41:21 | 显示全部楼层
RuCAM: Comparative Argumentative Machine for the Russian Languageexplain the choice and support it with arguments. ChatGPT-like models are able nowadays to generate a coherent answer in a natural language, however, they are not fully reliable as they are not publicly accessible and tend to hallucinate. Another solution is a Comparative Argument Machine (CAM), whi
发表于 2025-3-29 06:46:28 | 显示全部楼层
Paraphrasers and Classifiers: Controllable Text Generation for Text Style Transferetrained language models (LMs). However, the size of contemporary LMs often makes fine-tuning for downstream tasks infeasible. For this reason, methods of controllable text generation (CTG) which do not aim at fine-tuning the original LM have received attention for solving TST tasks. In this work, w
发表于 2025-3-29 10:07:50 | 显示全部楼层
发表于 2025-3-29 13:17:10 | 显示全部楼层
Unsupervised Ultra-Fine Entity Typing with Distributionally Induced Word Sensesity mention. Hence, automatic type generation is receiving increased interest, typically to be used as distant supervision data. In this study, we investigate an unsupervised way based on distributionally induced word senses. The types or labels are obtained by selecting the appropriate sense cluste
发表于 2025-3-29 17:52:03 | 显示全部楼层
发表于 2025-3-29 23:22:58 | 显示全部楼层
发表于 2025-3-30 03:49:52 | 显示全部楼层
Automatic Detection of Dialectal Features of Pskov Dialects in the Speech of Native Speakersristic of the Pskov dialects found on the territory of the Opochetsky district of the Pskov region and the Zapadnodvinsky district of the Tver region. The task is divided into two parts: speech recognition and features detection. First of all, we developed a model, the functionality of which include
发表于 2025-3-30 07:34:27 | 显示全部楼层
 关于派博传思  派博传思旗下网站  友情链接
派博传思介绍 公司地理位置 论文服务流程 影响因子官网 SITEMAP 大讲堂 北京大学 Oxford Uni. Harvard Uni.
发展历史沿革 期刊点评 投稿经验总结 SCIENCEGARD IMPACTFACTOR 派博系数 清华大学 Yale Uni. Stanford Uni.
|Archiver|手机版|小黑屋| 派博传思国际 ( 京公网安备110108008328) GMT+8, 2025-5-7 06:12
Copyright © 2001-2015 派博传思   京公网安备110108008328 版权所有 All rights reserved
快速回复 返回顶部 返回列表