https://github.com/huggingface/transformers
XLNet: Generalized Autoregressive Pretraining for Language Understanding
Papers with Code 아카이브
Ad-Hoc Information Retrieval
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 1
- 평가표
- 1
- 보존된 평가 기록
- 21
Ad-hoc information retrieval refers to the task of returning information resources related to a user query formulated in natural language.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/huggingface/xlnet
XLNet: Generalized Autoregressive Pretraining for Language Understanding
https://github.com/hwang1996/IRGAN-pytorch
IRGAN: A Minimax Game for Unifying Generative and Discriminative Information Retrieval Models
https://github.com/iYiYaHa/PyTorch-IRGAN
IRGAN: A Minimax Game for Unifying Generative and Discriminative Information Retrieval Models
https://github.com/irgroup/clef2023-longeval-irc
The Expando-Mono-Duo Design Pattern for Text Ranking with Pretrained Sequence-to-Sequence Models
https://github.com/jastfkjg/semantic-matching
https://github.com/jdxyw/deepKT
https://github.com/jonahwinninghoff/Text-Summarization
XLNet: Generalized Autoregressive Pretraining for Language Understanding
https://github.com/joshuaWang-bit/Textclassification-pytorch
XLNet: Generalized Autoregressive Pretraining for Language Understanding
https://github.com/kasys-lab/anserini-kasys
https://github.com/kaushaltrivedi/fast-bert
XLNet: Generalized Autoregressive Pretraining for Language Understanding
https://github.com/listenviolet/XLNet
XLNet: Generalized Autoregressive Pretraining for Language Understanding
https://github.com/littlewine/zeco2
ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT
https://github.com/lvyufeng/bert4ms/blob/master/bert4ms/models/xlnet.py
XLNet: Generalized Autoregressive Pretraining for Language Understanding
https://github.com/mihirs16/multi-stage-retrieval-using-rm3-and-t5
https://github.com/mikvrax/TrecingLab
https://github.com/nanzhaogang/contrib/tree/master/application/a-self-attentive-model-for-knowledge-tracing
https://github.com/neuralmind-ai/coliee
Document Ranking with a Pretrained Sequence-to-Sequence Model
https://github.com/nlpaueb/deep-relevance-ranking
Deep Relevance Ranking Using Enhanced Document-Query Interactions
https://github.com/oaqa/knn4qa
Traditional IR rivals neural models on the MS MARCO Document Ranking Leaderboard
https://github.com/osirrc/nvsm-docker
https://github.com/osirrc2019/nvsm-docker
https://github.com/parry-parry/pyterrier_t5
The Expando-Mono-Duo Design Pattern for Text Ranking with Pretrained Sequence-to-Sequence Models
https://github.com/pauldevos/python-notes
XLNet: Generalized Autoregressive Pretraining for Language Understanding
https://github.com/philipphager/baidu-bert-model
https://github.com/pl8787/DeepRank_PyTorch
https://github.com/pl8787/MatchPyramid-TensorFlow
https://github.com/pwc-1/Paper-9/tree/main/1/xlnet
XLNet: Generalized Autoregressive Pretraining for Language Understanding
https://github.com/pwc-1/Paper-9/tree/main/5/xlnet
XLNet: Generalized Autoregressive Pretraining for Language Understanding
https://github.com/rodgzilla/NVSM_pytorch
https://github.com/samwisegamjeee/pytorch-transformers
XLNet: Generalized Autoregressive Pretraining for Language Understanding
https://github.com/sebastian-hofstaetter/neural-ranking-drmm
https://github.com/shalini1194/SAKT
https://github.com/ssun32/clirmatrix_cedr
https://github.com/super-zhangchao/learning-to-match
https://github.com/terrierteam/pyterrier_t5
The Expando-Mono-Duo Design Pattern for Text Ranking with Pretrained Sequence-to-Sequence Models
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.