Papers with Code 아카이브
Word Sense Disambiguation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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The task of Word Sense Disambiguation (WSD) consists of associating words in context with their most suitable entry in a pre-defined sense inventory. The de-facto sense inventory for English in WSD is WordNet.. For example, given the word “mouse” and the following sentence:
“A mouse consists of an object held in one's hand, with one or more buttons.”
we would assign “mouse” with its electronic device sense (the 4th sense in the WordNet sense inventory).
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
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https://github.com/EightRice/atn_GPT-3
https://github.com/EleutherAI/gpt-neo
https://github.com/EleutherAI/lm-evaluation-harness
https://github.com/EleutherAI/lm_evaluation_harness
https://github.com/Garrafao/WUGs
https://github.com/Gozzo18/WSD-Final-Homework---NLP
https://github.com/HIT-SCIR/ELMoForManyLangs
https://github.com/Hironsan/anago
https://github.com/IMPLabUniPr/UniParma-at-semeval-2021-task-5
https://github.com/JHart96/keras_elmo_embedding_layer
https://github.com/JONGWE1/Paddle-DeBERTa
https://github.com/Jason-J-Choi/DeBERTa_TxtClassifier
https://github.com/JunnYu/x-transformers-paddle
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/KAGUYAHONGLAI/SRC
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/Ki6an/fastT5
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/LamLauChiu/Tensorflow_Learning
https://github.com/LeoLaugier/conditional-auto-encoder-text-to-text-transfer-transformer
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/MS-P3/code5/tree/main/t5
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/Mind23-2/MindCode-135
https://github.com/Mind23-2/MindCode-138
https://github.com/Mind23-2/MindCode-161
https://github.com/Mind23-2/MindCode-98
https://github.com/MindCode-4/code-3/tree/main/deberta
https://github.com/MindCode-4/code-3/tree/main/deberta_v2
https://github.com/MiuLab/xSense
https://github.com/NVIDIA/NeMo-Curator
https://github.com/Nimesh-Patel/text-to-text-transfer-transformer
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/PaddlePaddle/PaddleNLP/tree/develop/examples/language_model/gpt-3
https://github.com/PaddlePaddle/PaddleNLP/tree/develop/examples/language_model/t5
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/PrashantRanjan09/Elmo-Tutorial
https://github.com/PrashantRanjan09/WordEmbeddings-Elmo-Fasttext-Word2Vec
https://github.com/RUCAIBox/LLMBox
https://github.com/Ramos-Ramos/fruit-fly-net
https://github.com/RundongChou/elmo-chinese-oversimplified
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.