Pinned Repositories
Causal-Copilot
DCLR
DiffusionNAT
EACL2024: Diffusion-NAT: Self-Prompting Discrete Diffusion for Non-Autoregressive Text Generation
ELMoForManyLangs
Pre-trained ELMo Representations for Many Languages
KGSF
KDD2020 Improving Conversational Recommender Systems via Knowledge Graph based Semantic Fusion
lancelot39.github.io
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
MRC-models
The latest model of Machine Reader Comprehension, include match-LSTM, Bi-DAF, R-net, Mnemonic Reader
Pre-CRS
The code and data resource of CIKM2020 paper 《Leveraging Historical Interaction Data for ImprovingConversational Recommender System》
TG-ReDial
the dataset TG-ReDial
VDA
Virtual Data Augmentation: A Robust and General Framework for Fine-tuning Pre-trained Models
Lancelot39's Repositories
Lancelot39/KGSF
KDD2020 Improving Conversational Recommender Systems via Knowledge Graph based Semantic Fusion
Lancelot39/DCLR
Lancelot39/Causal-Copilot
Lancelot39/TG-ReDial
the dataset TG-ReDial
Lancelot39/Pre-CRS
The code and data resource of CIKM2020 paper 《Leveraging Historical Interaction Data for ImprovingConversational Recommender System》
Lancelot39/MRC-models
The latest model of Machine Reader Comprehension, include match-LSTM, Bi-DAF, R-net, Mnemonic Reader
Lancelot39/VDA
Virtual Data Augmentation: A Robust and General Framework for Fine-tuning Pre-trained Models
Lancelot39/DiffusionNAT
EACL2024: Diffusion-NAT: Self-Prompting Discrete Diffusion for Non-Autoregressive Text Generation
Lancelot39/ELMoForManyLangs
Pre-trained ELMo Representations for Many Languages
Lancelot39/lancelot39.github.io
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
Lancelot39/MarkdownPhoto
Lancelot39/MVS
The implementation code of the TOIS paper MVS "Enhancing Multi-View Smoothness for Sequential Recommendation Models"
Lancelot39/old_kunzhou.github.io
Kun Zhou的个人主页
Lancelot39/pyserini
Pyserini is a Python toolkit for reproducible information retrieval research with sparse and dense representations.