Topic: mrc Goto Github
Some thing interesting about mrc
Some thing interesting about mrc
mrc,Reasoning Shortcuts in MRC
Organization: alab-nii
mrc,Naver Boostcamp AI Tech Stage 3 : MRC (Machine Reading Comprehension)
Organization: bcaitech1
mrc,Twenty-Questions Game
Organization: boostcampaitech2
mrc,네이버 부스트캠프 | Open-Domain Question Answering(ODQA)
Organization: boostcampaitech3
mrc,基于层叠式注意力流的观点型阅读理解模型
User: caldreaming
mrc,Implement Maximal Ratio Combining & Equal Gain Combing & Selective Combining by Matlab
User: chenblue
mrc,Fixed some bugs and edited original baseline scripts from MS MARCO
User: chloeminkyung
mrc,In the field of Natural Language Processing, the detection of text toxicity has become a significant challenge. To facilitate the research in this sphere, one of the tasks of the International Workshop on Semantic Evaluation 2021 is Toxic Spans Detection. The essential objective of this task is to identify toxic spans within English passages. In this paper, two approaches for toxic spans detection considered: Machine Reading Comprehension and modified Named Entity Recognition approach altogether with Machine Reading Comprehension, but also these approaches are improved by Question Generation method. Furthermore, this research presents the exploratory analysis of provided data, proposes a training process and examines the analysis of the results on F1-score of new state-of-the-art BERT-based Language Models: BERT, ALBERT, RoBERTa, XLM-RoBERTa and SpanBERT. Finally, the best language model obtained an F1-score of 0.688 on the test data.
User: dmitrytsyu
mrc,中文NER的那些事儿
User: dsxiangli
mrc,“莱斯杯”全国第一届“军事智能·机器阅读”挑战赛[初赛top2版]
User: eguilg
mrc,基于 Tensorflow,仿 Scikit-Learn 设计的深度学习自然语言处理框架。支持 40 余种模型类,涵盖语言模型、文本分类、NER、MRC、知识蒸馏等各个领域
User: geyingli
mrc,A simple driver to control a MRC based robot with roboDK
User: glumb
mrc,indoor cycling workout creator. It generates .mrc, .erg, .zwo and .fit files from an specific text input file.
User: helderlopes
mrc,Analysis on the MS-MARCO leaderboard regarding the machine reading comprehension task.
User: indexfziq
mrc,Fast K-LRU Variable Object Size MRC Generation
User: jyang1997
mrc,특허분야 특화된 한국어 AI언어모델 KorPatBERT
User: kipi-ai
mrc,특허분야 특화된 한국어 AI언어모델 KorPatELECTRA
User: kipi-ai
mrc,This repo collects and re-produces models related to domains of question answering and machine reading comprehension
User: l11x0m7
mrc,A PyTorch implemention of Match-LSTM, R-NET and M-Reader for Machine Reading Comprehension
User: laddie132
mrc,a version of Match-LSTM+ for CMRC dataset
User: laddie132
mrc,机器阅读理解 冠军/亚军代码及中文预训练MRC模型
User: luhua-rain
mrc,2021语言与智能技术竞赛:机器阅读理解任务
User: lyj555
mrc,Liveability of Melbourne
User: melodyjin-y
mrc,2020 科大讯飞 事件抽取挑战赛
User: menghuanlater
mrc,Transformer-based machine reading comprehension in combination with Azure Cognitive Search
Organization: microsoft
mrc,Machine Reading Comprehension special for the Vietnamese language
User: nguyenvulebinh
mrc,ODQA Demo Site
Organization: odqa-team-tajo
mrc,네이버 부스트 캠프 AI TECH, P3 MRC Project
Organization: odqa-team-tajo
mrc,MRC Compressor based on PassportPDF.
Organization: orpalis
Home Page: https://passportpdf.com/
mrc,Self Question-answering: Aspect-based Sentiment Analysis by Role Flipped Machine Reading Comprehension
User: phanxuanphucnd
mrc,Read and write files and manipulate data in the MRC2014 format
User: sethaxen
mrc,Embedding, NMT, Text_Classification, Text_Generation, NER etc.
User: shawroad
mrc,Evaluation framework for open-domain question answering.
Organization: soco-ai
mrc,Machine Reading Comprehension
User: sunyanhust
mrc,Part of the 7th solution of the Kaggle Tweet Sentiment Extraction competition
User: thuwyh
mrc,Baseline code for Korean open domain question answering(ODQA)
Organization: vumblebot
Home Page: https://bit.ly/3fvgZZ0
mrc,科赛网-莱斯杯:全国第二届“军事智能机器阅读”挑战赛 前十团队PPT文档代码总结
User: yingziqiang
mrc,Multilingual Multi-Aspect Explainability Analyses on Machine Reading Comprehension Models (iScience)
User: ymcui
Home Page: https://www.cell.com/iscience/fulltext/S2589-0042(22)00446-1
mrc,阅读/论文笔记
User: yongbowin
mrc,Worth-reading paper list and other awesome resources on Machine Reading Comprehension (MRC) and textual Question Answering (QA). 机器阅读理解与文本问答领域值得一读的论文列表和其他相关资源集合
User: zhengzixiang
mrc,An Open-Source Toolkit for Machine Reading Comprehension and Textual Question Answering Based on PyTorch. 基于PyTorch的机器阅读理解与文本问答开源工具
User: zhengzixiang
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