René's URL Explorer Experiment


Title: GitHub - microsoft/KC: Knowledge Computing group - MSRA · GitHub

Open Graph Title: GitHub - microsoft/KC: Knowledge Computing group - MSRA

X Title: GitHub - microsoft/KC: Knowledge Computing group - MSRA

Description: Knowledge Computing group - MSRA. Contribute to microsoft/KC development by creating an account on GitHub.

Open Graph Description: Knowledge Computing group - MSRA. Contribute to microsoft/KC development by creating an account on GitHub.

X Description: Knowledge Computing group - MSRA. Contribute to microsoft/KC development by creating an account on GitHub.

Mail addresses
opencode@microsoft.com

Opengraph URL: https://github.com/microsoft/KC

X: @github

direct link

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GitHub CopilotWrite better code with AIhttps://github.com/features/copilot
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CODE_OF_CONDUCT.mdhttps://github.com/microsoft/KC/blob/main/CODE_OF_CONDUCT.md
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READMEhttps://github.com/microsoft/KC
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MIT licensehttps://github.com/microsoft/KC
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Knowledge Computing (KC)https://www.microsoft.com/en-us/research/group/knowledge-computing/
Internship opportunities in KChttps://www.microsoft.com/en-us/research/uploads/prod/2020/12/kc_intern_job_description_2020.pdf
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https://github.com/microsoft/KC#news
Recognizers-Text projecthttps://github.com/microsoft/Recognizers-Text
MLKD OODhttps://github.com/microsoft/KC/tree/main/papers/MLKD_OOD
CoLaDahttps://github.com/microsoft/vert-papers/tree/master/papers/CoLaDa
TACRhttps://arxiv.org/abs/2305.14682
Recognizers-Text projecthttps://github.com/microsoft/Recognizers-Text
Generalizable Question Answering (GrailQA)https://dki-lab.github.io/GrailQA/
LinkingPark systemhttps://github.com/microsoft/vert-papers/tree/master/papers/LinkingPark
Recognizers-Text projecthttps://github.com/microsoft/Recognizers-Text
Recognizers-Text projecthttps://github.com/microsoft/Recognizers-Text
Generalizable Question Answering (GrailQA) leaderboardhttps://dki-lab.github.io/GrailQA/
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LinkingParkhttps://www.microsoft.com/en-us/research/publication/linkingpark-an-integrated-approach-for-semantic-table-interpretation/
SemTab 2020 challenge (Semantic Web Challenge on Tabular Data to Knowledge Graph Matching)https://www.cs.ox.ac.uk/isg/challenges/sem-tab/2020/results.html
https://github.com/microsoft/KC#recent-papers
Multi-Level Knowledge Distillation for Out-of-Distribution Detection in Texthttps://aclanthology.org/2023.acl-long.403/
https://github.com/microsoft/KC/tree/main/papers/MLKD_OODhttps://github.com/microsoft/KC/tree/main/papers/MLKD_OOD
ColaDa: A Collaborative Label Denoising Framework for Cross-lingual Named Entity Recognitionhttps://aclanthology.org/2023.acl-long.330/
https://github.com/microsoft/vert-papers/tree/master/papers/CoLaDahttps://github.com/microsoft/vert-papers/tree/master/papers/CoLaDa
TACR: A Table-alignment-based Cell-selection and Reasoning Model for Hybrid Question-Answeringhttps://aclanthology.org/2023.findings-acl.409.pdf
TIARA: Multi-grained Retrieval for Robust Question Answering over Large Knowledge Baseshttps://arxiv.org/abs/2210.12925
https://github.com/microsoft/KC/tree/master/papers/TIARAhttps://github.com/microsoft/KC/tree/master/papers/TIARA
LinkingPark: An Automatic Semantic Table Interpretation Systemhttps://www.sciencedirect.com/science/article/abs/pii/S1570826822000233
https://github.com/microsoft/vert-papers/tree/master/papers/LinkingParkhttps://github.com/microsoft/vert-papers/tree/master/papers/LinkingPark
Rows from Many Sources: Enriching row completions from Wikidata with a pre-trained Language Modelhttps://arxiv.org/abs/2204.07014
On the Effectiveness of Sentence Encoding for Intent Detection Meta-Learninghttps://arxiv.org/abs/X
https://github.com/microsoft/KC/tree/master/papers/IDMLhttps://github.com/microsoft/KC/tree/master/papers/IDML
Decomposed Meta-Learning for Few-Shot Named Entity Recognitionhttps://arxiv.org/abs/2204.05751
https://github.com/microsoft/vert-papers/tree/master/papers/DecomposedMetaNERhttps://github.com/microsoft/vert-papers/tree/master/papers/DecomposedMetaNER
AdvPicker: Effectively Leveraging Unlabeled Data via Adversarial Discriminator for Cross-Lingual NERhttps://arxiv.org/abs/2106.02300
https://github.com/microsoft/vert-papers/tree/master/papers/AdvPickerhttps://github.com/microsoft/vert-papers/tree/master/papers/AdvPicker
ReTraCk: A Flexible and Efficient Framework for Knowledge Base Question Answeringhttps://aclanthology.org/2021.acl-demo.39/
https://github.com/microsoft/KC/tree/master/papers/ReTraCkhttps://github.com/microsoft/KC/tree/master/papers/ReTraCk
Issues with Entailment-based Zero-shot Text Classificationhttps://aclanthology.org/2021.acl-short.99/
https://github.com/microsoft/KC/tree/master/papers/Entailment-Issueshttps://github.com/microsoft/KC/tree/master/papers/Entailment-Issues
BoningKnife: Joint Entity Mention Detection and Typing for Nested NER via prior Boundary Knowledgehttps://arxiv.org/abs/2107.09429
LinkingPark: An integrated approach for Semantic Table Interpretationhttp://ceur-ws.org/Vol-2775/paper7.pdf
https://github.com/microsoft/vert-papers/tree/master/papers/LinkingParkhttps://github.com/microsoft/vert-papers/tree/master/papers/LinkingPark
UniTrans: Unifying Model Transfer and Data Transfer for Cross-Lingual Named Entity Recognition with Unlabeled Datahttps://www.ijcai.org/Proceedings/2020/543
https://github.com/microsoft/vert-papers/tree/master/papers/UniTranshttps://github.com/microsoft/vert-papers/tree/master/papers/UniTrans
Single-/Multi-Source Cross-Lingual NER via Teacher-Student Learning on Unlabeled Data in Target Languagehttps://arxiv.org/abs/2004.12440
https://github.com/microsoft/vert-papers/tree/master/papers/SingleMulti-TShttps://github.com/microsoft/vert-papers/tree/master/papers/SingleMulti-TS
Enhanced Meta-Learning for Cross-lingual Named Entity Recognition with Minimal Resourceshttps://arxiv.org/abs/1911.06161
https://github.com/microsoft/vert-papers/tree/master/papers/Meta-Crosshttps://github.com/microsoft/vert-papers/tree/master/papers/Meta-Cross
Improving Entity Linking by Modeling Latent Entity Type Informationhttps://arxiv.org/abs/2001.01447
Exploring Word Representations on Time Expression Recognitionhttps://www.cs.virginia.edu/~sc3hn/bert-time.pdf
Towards Improving Neural Named Entity Recognition with Gazetteershttps://www.aclweb.org/anthology/P19-1524/
https://github.com/microsoft/vert-papers/tree/master/papers/SubTaggerhttps://github.com/microsoft/vert-papers/tree/master/papers/SubTagger
CAN-NER: Convolutional Attention Network for Chinese Named Entity Recognitionhttps://arxiv.org/abs/1904.02141
https://github.com/microsoft/vert-papers/tree/master/papers/CAN-NERhttps://github.com/microsoft/vert-papers/tree/master/papers/CAN-NER
GRN: Gated Relation Network to Enhance Convolutional Neural Network for Named Entity Recognitionhttps://arxiv.org/abs/1907.05611
https://github.com/microsoft/vert-papers/tree/master/papers/GRN-NERhttps://github.com/microsoft/vert-papers/tree/master/papers/GRN-NER
https://github.com/microsoft/KC#related-projects
VERT (Versatile Entity Recognition & Disambiguation Toolkit)https://github.com/microsoft/vert-papers
microsoft/Recognizers-Texthttps://github.com/microsoft/Recognizers-Text
https://github.com/microsoft/KC#contributing
https://cla.opensource.microsoft.comhttps://cla.opensource.microsoft.com
Microsoft Open Source Code of Conducthttps://opensource.microsoft.com/codeofconduct/
Code of Conduct FAQhttps://opensource.microsoft.com/codeofconduct/faq/
https://github.com/microsoft/KC#trademarks
Microsoft's Trademark & Brand Guidelineshttps://www.microsoft.com/en-us/legal/intellectualproperty/trademarks/usage/general
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