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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/joytianya/google_bert

Attention Is All You Need

https://github.com/jsantoso2/yelp-clone-ml-project

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

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

Language Models are Few-Shot Learners

https://github.com/jungomi/swiss-language-model

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

https://github.com/junhahyung/bert_finetune

Attention Is All You Need

https://github.com/junhahyung/bert_transfer

Attention Is All You Need

https://github.com/junnyu/paddle_t5

Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

https://github.com/jzhang38/tinyllama

Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling

https://github.com/kafura-kafiri/tf2-elmo

Deep contextualized word representations

https://github.com/kaist-dmlab/BioNER

Deep contextualized word representations

https://github.com/kaituoxu/Speech-Transformer

Attention Is All You Need

https://github.com/kaituoxu/SpeechTransformer

Attention Is All You Need

https://github.com/kamalkraj/BERT-SQuAD

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

https://github.com/kamalkraj/BERT_NER

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

https://github.com/kapllan/zeroshot_lexglue

Scaling Instruction-Finetuned Language Models

https://github.com/karenacorn99/explore-bert

Attention Is All You Need

https://github.com/karpathy/build-nanogpt

Language Models are Few-Shot Learners

https://github.com/karpathy/llm.c

Language Models are Few-Shot Learners

https://github.com/karpathy/makemore

Attention Is All You Need

https://github.com/karpathy/minGPT

Attention Is All You Need

https://github.com/karta282950/bert-multiclass

Attention Is All You Need

https://github.com/kaushaltrivedi/fast-bert

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

https://github.com/keiyamashita111/aaproject

Attention Is All You Need

https://github.com/kelly2016/multi-label-bert

Attention Is All You Need

https://github.com/keonlee9420/Parallel-Tacotron2

Attention Is All You Need

https://github.com/kh-kim/simple-nmt

Attention Is All You Need

https://github.com/khalidsaifullaah/bertify

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

https://github.com/khwajawisal/Attention-augmented-Convolutional-Neural-Networks

Attention Is All You Need

https://github.com/kiko441500/google_bert

Attention Is All You Need

https://github.com/kingcheng2000/bert

Attention Is All You Need

https://github.com/kingcong/gpu_albert

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

https://github.com/kinimod23/NMT_Project

Deep contextualized word representations

https://github.com/kkjawz/coref-ee

Higher-order Coreference Resolution with Coarse-to-fine Inference

https://github.com/knotgrass/attention/blob/main/attn/attention.py

Attention Is All You Need

https://github.com/knuddj1/op_text

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

https://github.com/knuddy/op_text

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

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