https://github.com/AI4Bharat/indic-bart
공식 코드IndicBART: A Pre-trained Model for Indic Natural Language Generation
Papers with Code 아카이브
Extreme Summarization
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 20
Image credit: TLDR: Extreme Summarization of Scientific Documents
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/allenai/scitldr
공식 코드https://github.com/declare-lab/wikides
공식 코드WikiDes: A Wikipedia-Based Dataset for Generating Short Descriptions from Paragraphs
https://github.com/google-research/byt5
공식 코드ByT5: Towards a token-free future with pre-trained byte-to-byte models
https://github.com/iDEA-iSAIL-Lab-UIUC/APEX
공식 코드APEX$^2$: Adaptive and Extreme Summarization for Personalized Knowledge Graphs
https://github.com/morningmoni/citesum
공식 코드https://github.com/sajastu/reddit_collector
공식 코드TLDR9+: A Large Scale Resource for Extreme Summarization of Social Media Posts
https://github.com/shashiongithub/XSum
공식 코드https://github.com/sobamchan/rougek
공식 코드https://github.com/sobamchan/xscitldr
공식 코드X-SCITLDR: Cross-Lingual Extreme Summarization of Scholarly Documents
https://github.com/yaolu/Multi-XScience
공식 코드https://github.com/2024-MindSpore-1/Code2/tree/main/model-1/byt5
ByT5: Towards a token-free future with pre-trained byte-to-byte models
https://github.com/EdinburghNLP/XSum
https://github.com/UH-SERG/SIVAND
A Convolutional Attention Network for Extreme Summarization of Source Code
https://github.com/bentrevett/extreme-summarization-of-source-code
A Convolutional Attention Network for Extreme Summarization of Source Code
https://github.com/bnitsan/papertweet
https://github.com/chrisociepa/allamo
https://github.com/conceptofmind/PaLM-flax
https://github.com/foundation-model-stack/fms-fsdp
https://github.com/google/paxml
https://github.com/huggingface/transformers/tree/master/src/transformers/models/byt5
ByT5: Towards a token-free future with pre-trained byte-to-byte models
https://github.com/iamgroot42/mimir
https://github.com/jungokasai/twist_decoding
https://github.com/lucidrains/CoCa-pytorch
https://github.com/lucidrains/PaLM-jax
https://github.com/lucidrains/PaLM-pytorch
https://github.com/mdrafiqulrabin/SIVAND
A Convolutional Attention Network for Extreme Summarization of Source Code
https://github.com/mdrafiqulrabin/tnpa-generalizability
A Convolutional Attention Network for Extreme Summarization of Source Code
https://github.com/pltrdy/extoracle_summarization
https://github.com/pwc-1/Paper-5/tree/main/mbart50
IndicBART: A Pre-trained Model for Indic Natural Language Generation
https://github.com/pwc-1/Paper-9/tree/main/2/mbart50
IndicBART: A Pre-trained Model for Indic Natural Language Generation
https://github.com/samialabed/method-name-prediction
A Convolutional Attention Network for Extreme Summarization of Source Code
https://github.com/ufal/multilexnorm2021
ByT5: Towards a token-free future with pre-trained byte-to-byte models
https://github.com/yoreG123/Paddle-ByT5
ByT5: Towards a token-free future with pre-trained byte-to-byte models
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.