https://github.com/MS-P3/code7/tree/main/xlnet
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
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- 평가표
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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/Machine-Learning-for-Everyone-ML4E/CoP-Code-of-Papers
https://github.com/MatanRad/Neural-IR-Project
PACRR: A Position-Aware Neural IR Model for Relevance Matching
https://github.com/Mind23-2/MindCode-149
Simplified TinyBERT: Knowledge Distillation for Document Retrieval
https://github.com/MindCode-4/code-11/tree/main/a-self-attentive-model-for-knowledge-tracing
https://github.com/MindCode-4/code-5/tree/main/xlnet
XLNet: Generalized Autoregressive Pretraining for Language Understanding
https://github.com/MindCode-4/code-6/tree/main/a-self-attentive-model-for-knowledge-tracing
https://github.com/MindSpore-paper-code-3/code9/tree/main/tinybert
Simplified TinyBERT: Knowledge Distillation for Document Retrieval
https://github.com/MindSpore-scientific/code-3/tree/main/a-self-attentive-model-for-knowledge-tracing
https://github.com/MulukenW/test
https://github.com/NathanDuran/Sentence-Encoding-for-DA-Classification
XLNet: Generalized Autoregressive Pretraining for Language Understanding
https://github.com/PaddlePaddle/PaddleNLP/tree/develop/examples/language_model/xlnet
XLNet: Generalized Autoregressive Pretraining for Language Understanding
https://github.com/PaddlePaddle/PaddleRec/tree/release/2.1.0/models/match/match-pyramid
https://github.com/SJHBXShub/Question_pair
https://github.com/SambhawDrag/XLNet.jl
XLNet: Generalized Autoregressive Pretraining for Language Understanding
https://github.com/TikaToka/CapstoneSpring
https://github.com/arshadshk/SAKT-pytorch
https://github.com/bmitra-msft/NDRM
Learning to Match Using Local and Distributed Representations of Text for Web Search
https://github.com/castorini/Anserini
https://github.com/castorini/birch
https://github.com/castorini/docTTTTTquery
https://github.com/castorini/duobert
https://github.com/castorini/pygaggle
Document Ranking with a Pretrained Sequence-to-Sequence Model
https://github.com/castorini/rank_llm
The Expando-Mono-Duo Design Pattern for Text Ranking with Pretrained Sequence-to-Sequence Models
https://github.com/chesterdu/contrastive_summary
XLNet: Generalized Autoregressive Pretraining for Language Understanding
https://github.com/cmacdonald/pyterrier_colbert
ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT
https://github.com/crystina-z/CEDR_tpu
https://github.com/cuhksz-nlp/SAPar
XLNet: Generalized Autoregressive Pretraining for Language Understanding
https://github.com/cxa-unique/Simplified-TinyBERT
Simplified TinyBERT: Knowledge Distillation for Document Retrieval
https://github.com/expertailab/spaceqa
ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT
https://github.com/facebookresearch/anli
XLNet: Generalized Autoregressive Pretraining for Language Understanding
https://github.com/fanchenyou/transformer-study
XLNet: Generalized Autoregressive Pretraining for Language Understanding
https://github.com/faneshion/DRMM
https://github.com/graykode/xlnet-Pytorch
XLNet: Generalized Autoregressive Pretraining for Language Understanding
https://github.com/hamed-zamani/snrm
https://github.com/https-seyhan/BugAI
XLNet: Generalized Autoregressive Pretraining for Language Understanding
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.