https://github.com/markustyj/fsponer_ecai2024
공식 코드FsPONER: Few-shot Prompt Optimization for Named Entity Recognition in Domain-specific Scenarios
Papers with Code 아카이브
NER
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The named entity recognition (NER) involves identification of key information in the text and classification into a set of predefined categories. This includes standard entities in the text like Part of Speech (PoS) and entities like places, names etc...
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/masakhane-io/masakhane-ner
공식 코드https://github.com/masakhane-io/masakhane-ner/tree/main/MasakhaNER2.0
공식 코드MasakhaNER 2.0: Africa-centric Transfer Learning for Named Entity Recognition
https://github.com/masoud-monajati/llm_bio_ner
공식 코드LLMs in Biomedicine: A study on clinical Named Entity Recognition
https://github.com/matejklemen/morphological-comment-filtering
공식 코드Enhancing deep neural networks with morphological information
https://github.com/matejklemen/morphological-dependency-parsing
공식 코드Enhancing deep neural networks with morphological information
https://github.com/mckysse/gain
공식 코드https://github.com/mckysse/msd
공식 코드https://github.com/mebzmoren/cebuaner
공식 코드CebuaNER: A New Baseline Cebuano Named Entity Recognition Model
https://github.com/mehdibenamorr/Token-Positional-Bias
공식 코드Technical Report: Impact of Position Bias on Language Models in Token Classification
https://github.com/mehdibenamorr/bert-positional-bias-ner
공식 코드Technical Report: Impact of Position Bias on Language Models in Token Classification
https://github.com/melelbgu/sage
공식 코드https://github.com/mhtang1995/bopn
공식 코드A Boundary Offset Prediction Network for Named Entity Recognition
https://github.com/microsoft/Unicoder
공식 코드XLM-K: Improving Cross-Lingual Language Model Pre-training with Multilingual Knowledge
https://github.com/microsoft/binder
공식 코드Optimizing Bi-Encoder for Named Entity Recognition via Contrastive Learning
https://github.com/microsoft/genalog
공식 코드Lights, Camera, Action! A Framework to Improve NLP Accuracy over OCR documents
https://github.com/microsoft/scglab
공식 코드https://github.com/microsoft/vert-papers
공식 코드CoLaDa: A Collaborative Label Denoising Framework for Cross-lingual Named Entity Recognition
https://github.com/microsoft/vert-papers/tree/master/papers/AdvPicker
공식 코드AdvPicker: Effectively Leveraging Unlabeled Data via Adversarial Discriminator for Cross-Lingual NER
https://github.com/microsoft/vert-papers/tree/master/papers/CAN-NER
공식 코드CAN-NER: Convolutional Attention Network for Chinese Named Entity Recognition
https://github.com/microsoft/vert-papers/tree/master/papers/GRN-NER
공식 코드GRN: Gated Relation Network to Enhance Convolutional Neural Network for Named Entity Recognition
https://github.com/microsoft/vert-papers/tree/master/papers/Meta-Cross
공식 코드Enhanced Meta-Learning for Cross-lingual Named Entity Recognition with Minimal Resources
https://github.com/microsoft/vert-papers/tree/master/papers/SingleMulti-TS
공식 코드https://github.com/microsoft/vert-papers/tree/master/papers/UniTrans
공식 코드https://github.com/microsoft/xtreme-distil-transformers
공식 코드XtremeDistilTransformers: Task Transfer for Task-agnostic Distillation
https://github.com/milangritta/Pragmatic-Guide-to-Geoparsing-Evaluation
공식 코드https://github.com/minghao-wu/CRF-AE
공식 코드Evaluating the Utility of Hand-crafted Features in Sequence Labelling
https://github.com/modelscope/adaseq
공식 코드DAMO-NLP at NLPCC-2022 Task 2: Knowledge Enhanced Robust NER for Speech Entity Linking
https://github.com/mohammadKhalifa/zero-shot-arabic-dialects
공식 코드https://github.com/moncefbenaicha/spoken-ner
공식 코드Leveraging Cross-Lingual Transfer Learning in Spoken Named Entity Recognition Systems
https://github.com/monikkinom/ner-lstm
공식 코드Towards Deep Learning in Hindi NER: An approach to tackle the Labelled Data Scarcity
https://github.com/mushfiqur11/tokenfreetransfer
공식 코드To token or not to token: A Comparative Study of Text Representations for Cross-Lingual Transfer
https://github.com/mykelismyname/mslm
공식 코드https://github.com/naiveneuron/wikigoldsk
공식 코드https://github.com/napsternxg/NER_bias
공식 코드https://github.com/nasimisu/truth-discovery-in-sequence-labels-from-crowds
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.