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Visual Storytelling
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
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- 보존된 평가 기록
- 33
<span style="color:grey; opacity: 0.6">( Image credit: No Metrics Are Perfect )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/bplank/teaching-dl4nlp
Effective Approaches to Attention-based Neural Machine Translation
https://github.com/brainsqueeze/text2vec
https://github.com/brandontrabucco/scaled_dot_product_attention
https://github.com/brightmart/bert_customized
https://github.com/brightmart/bert_original
https://github.com/bshantam97/Attention_Based_Networks
https://github.com/bytedance/neurst
https://github.com/bzhangGo/zero
https://github.com/cadia-lvl/fastspeech2
https://github.com/cahya-wirawan/indonesian-language-models
https://github.com/camlaedtke/NLP
https://github.com/caoyujiALgLM/NLP
https://github.com/caoyujiALgLM/NLP-progress
https://github.com/chalothon/BERT_Practice
https://github.com/chandu7077/mybert
https://github.com/chao-ji/tf-seq2seq
Effective Approaches to Attention-based Neural Machine Translation
https://github.com/chen-xiong-yi/OwnBERT
https://github.com/chengchingwen/transformers.jl
https://github.com/chiayewken/bert-qa
https://github.com/chrisleunglokhin/Capstone-BERT
https://github.com/christianspybrook/article_recommender
https://github.com/cloudmcloudyo/capstone
https://github.com/cmsflash/efficient-attention
https://github.com/coco60/bert-test
https://github.com/colorfulscoop/tfdlg
https://github.com/conceptofmind/LaMDA-pytorch
https://github.com/conceptofmind/lamda-rlhf-pytorch
https://github.com/coronazap/bert_client
https://github.com/cosmoquester/seq2seq
https://github.com/cospplay/bert-master
https://github.com/coxy1989/tfmr
https://github.com/cpm0722/transformer_pytorch
https://github.com/cuber2460/bert
https://github.com/cyberzhg/keras-pos-embd
https://github.com/czero69/acomoeye-NN
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