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Coreference Resolution

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하위 태스크: 2
평가표: 16
보존된 평가 기록: 154

Coreference resolution is the task of clustering mentions in text that refer to the same underlying real world entities.

Example:

               +-----------+
               |           |
I voted for Obama because he was most aligned with my values", she said.
 |                                                 |            |
 +-------------------------------------------------+------------+

"I", "my", and "she" belong to the same cluster and "Obama" and "he" belong to the same cluster.

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/monimoyd/NLPMachineTranslationUsingTransformer

Attention Is All You Need

https://github.com/moon23k/Scheduled_Sampling

Attention Is All You Need

https://github.com/moon23k/Transformer_Anchors

Attention Is All You Need

https://github.com/moon23k/Transformer_Archs

Attention Is All You Need

https://github.com/mpandeydev/SDnetmod

SDNet: Contextualized Attention-based Deep Network for Conversational Question Answering

https://github.com/mtzcorporations/nlp_teamjodka

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/musixmatchresearch/umberto

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/myamamoto555/tf-bert

Attention Is All You Need

https://github.com/nachiketaa/BERT-pytorch

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/nachiketaa/bert

Attention Is All You Need

https://github.com/nageshsinghc4/deepwrap

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/nalbarr/coursera-ai4med-course3

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/nameoverflow/neuro-cangjie

Attention Is All You Need

https://github.com/natel9178/transformer-refork

Attention Is All You Need

https://github.com/national-center-for-ai-saudi-arabia/lm-evaluation-harness

Language Models are Few-Shot Learners

https://github.com/ncoop57/gpt-code-clippy

Language Models are Few-Shot Learners

https://github.com/neburseni/NLP

Attention Is All You Need

https://github.com/neqkir/attention-mechanism

Attention Is All You Need

https://github.com/nerdimite/bert-finetuning-webinar

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/neuralmagic/lm-evaluation-harness

Language Models are Few-Shot Learners

https://github.com/neuralmind-ai/coliee

DeBERTa: Decoding-enhanced BERT with Disentangled Attention

https://github.com/ngocphucck/BERT-questions-classification

Attention Is All You Need

https://github.com/niccolot/ENG-ITA_NMT

Attention Is All You Need

https://github.com/nicholasbao/nlp_job

Attention Is All You Need

https://github.com/nicolashernandez/readi-lrec22

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/nietao2/DeepSpeechRecognition

Attention Is All You Need

https://github.com/nlinc1905/dsilt-tsa

Attention Is All You Need

https://github.com/nlp-research/bilm-tf

Deep contextualized word representations

https://github.com/nlx-group/overlapy

Language Models are Few-Shot Learners

https://github.com/nmfisher/bert-modified

Attention Is All You Need

https://github.com/noelkelias/multitok

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/noise-learning/selfmix

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/noriyukipy/tfchat

Attention Is All You Need

https://github.com/noriyukipy/tfdlg

Attention Is All You Need

https://github.com/nrc-cnrc/sockeye-multisource

Attention Is All You Need

https://github.com/nsfzyzz/generalization_metrics_for_nlp

Attention Is All You Need

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