https://github.com/google-research/google-research/tree/master/etcsum
공식 코드Stepwise Extractive Summarization and Planning with Structured Transformers
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/google-research/google-research/tree/master/felix
공식 코드https://github.com/google-research/google-research/tree/master/smith
공식 코드https://github.com/google-research/language
공식 코드Pretraining with Contrastive Sentence Objectives Improves Discourse Performance of Language Models
https://github.com/google-research/lasertagger
공식 코드https://github.com/google-research/scenic
공식 코드https://github.com/google-research/scenic/tree/main/scenic/projects/vid2seq
공식 코드Vid2Seq: Large-Scale Pretraining of a Visual Language Model for Dense Video Captioning
https://github.com/google-research/tapas
공식 코드https://github.com/google-research/xtreme
공식 코드XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalization
https://github.com/google/retrieval-qa-eval
공식 코드https://github.com/goru001/inltk
공식 코드https://github.com/gotutiyan/gec-metrics
공식 코드https://github.com/gouwsmeister/bilbowa
공식 코드BilBOWA: Fast Bilingual Distributed Representations without Word Alignments
https://github.com/gowitheflow-1998/la-ser-cubed
공식 코드Length is a Curse and a Blessing for Document-level Semantics
https://github.com/gowitheflow-1998/on-isotropy-of-contrastive-srl
공식 코드https://github.com/gowitheflow-1998/pixel-linguist
공식 코드https://github.com/gpengzhi/Bi-SimCut
공식 코드Bi-SimCut: A Simple Strategy for Boosting Neural Machine Translation
https://github.com/gpengzhi/CrossConST-MT
공식 코드https://github.com/gpengzhi/crossconst-sr
공식 코드Learning Multilingual Sentence Representations with Cross-lingual Consistency Regularization
https://github.com/greenparachute/probing-with-noise
공식 코드Probing with Noise: Unpicking the Warp and Weft of Embeddings
https://github.com/gringham/bmx
공식 코드BMX: Boosting Natural Language Generation Metrics with Explainability
https://github.com/grmarco/the-reader-is-the-metric
공식 코드https://github.com/grndnl/w266_final_project
공식 코드On the effectiveness of Large Language Models in the mechanical design domain
https://github.com/grushaprasad/RNN-Priming
공식 코드Using Priming to Uncover the Organization of Syntactic Representations in Neural Language Models
https://github.com/gstoica27/JRRELP
공식 코드Improving Relation Extraction by Leveraging Knowledge Graph Link Prediction
https://github.com/gstoica27/Re-TACRED
공식 코드https://github.com/gt-salt/positive-frames
공식 코드https://github.com/gtfintechlab/worldcentralbanks
공식 코드Words That Unite The World: A Unified Framework for Deciphering Central Bank Communications Globally
https://github.com/gtshs2/BetaLSTM
공식 코드https://github.com/guardiaum/BERT-SIDE
공식 코드Distantly-Supervised Neural Relation Extraction with Side Information using BERT
https://github.com/gucci-j/light-transformer-emnlp2021
공식 코드Frustratingly Simple Pretraining Alternatives to Masked Language Modeling
https://github.com/gucorpling/GumDrop
공식 코드https://github.com/gucorpling/discodisco
공식 코드https://github.com/gugu511yy/ptq4ris
공식 코드PTQ4RIS: Post-Training Quantization for Referring Image Segmentation
https://github.com/guolinke/TUPE
공식 코드https://github.com/guotong1988/Semantic-Tree-Search
공식 코드Revisiting Semantic Representation and Tree Search for Similar Question Retrieval
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.