Papers with Code 아카이브
Abstractive Text Summarization
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
- 20
- 보존된 평가 기록
- 98
Abstractive Text Summarization is the task of generating a short and concise summary that captures the salient ideas of the source text. The generated summaries potentially contain new phrases and sentences that may not appear in the source text.
Source: Generative Adversarial Network for Abstractive Text Summarization
Image credit: Abstractive Text Summarization using Sequence-to-sequence RNNs and Beyond
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/hfxunlp/transformer
https://github.com/hihellohowareyou/RESREF_Chatbot_data_for_Korean
https://github.com/hiun/learning-transformers
https://github.com/hoangtrungchinh/Bert-SQuAD-v2
https://github.com/hrbigelow/transformer-aiayn
https://github.com/hrlinlp/coconet
https://github.com/https-github-com-GiangHoang9912/ernie-gen
https://github.com/huangxt39/BART_on_COVID_dialogue
https://github.com/hubiodatalab/druggen
https://github.com/huffon/factsumm
Asking and Answering Questions to Evaluate the Factual Consistency of Summaries
https://github.com/huggingface/transformers
https://github.com/hyunwookl/testam
https://github.com/hyunwoongko/transformer
https://github.com/i2r-simmc/i2r-simmc-2020
https://github.com/iamgroot42/mimir
https://github.com/ibm/graph_ensemble_learning
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/ibrahim-elsawy/test
PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization
https://github.com/icewing1996/bert_dep
https://github.com/ictnlp/DiverseNMT
https://github.com/ictnlp/NA-MNMT
https://github.com/ictnlp/PTE-NMT
https://github.com/ictnlp/TLAT-NMT
https://github.com/idiotprofessorchen/bert.github.io
https://github.com/iejMac/ScriptWriter
https://github.com/iinemo/lm-polygraph
Mutual Information Alleviates Hallucinations in Abstractive Summarization
https://github.com/ikergarcia1996/Simultaneous-Machine-Translation
https://github.com/insigh/THUMT
https://github.com/ionnoant/DS8008-final-project
https://github.com/ishritam/Image-captioning-with-visual-attention
https://github.com/ishtoo1/Text-Summarization-using-Attention
Get To The Point: Summarization with Pointer-Generator Networks
https://github.com/ishtoo1/Text-Summarization-using-Pointer-Generator-Model
Get To The Point: Summarization with Pointer-Generator Networks
https://github.com/itzprashu1/prashant
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/iwangjian/textsum-gan
Generative Adversarial Network for Abstractive Text Summarization
https://github.com/j40903272/bottom-up-summary
https://github.com/jackaduma/ChatGLM-LoRA-RLHF-PyTorch
GLM: General Language Model Pretraining with Autoregressive Blank Infilling
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.