lisa-sicuan

lisa-sicuan's Stars

• DOsinga/deep_learning_cookbook

  Deep Learning Cookbox

  Language:Jupyter Notebook6883766336

• thunlp/DocRED

  Dataset and codes for ACL 2019 DocRED: A Large-Scale Document-Level Relation Extraction Dataset.

  Language:Python6131880113

• THUDM/CogQA

  Source code and dataset for ACL 2019 paper "Cognitive Graph for Multi-Hop Reading Comprehension at Scale"

  Language:Python455193982

• Cartus/AGGCN

  Attention Guided Graph Convolutional Networks for Relation Extraction (authors' PyTorch implementation for the ACL19 paper)

  Language:Python43274088

• jasonwu0731/trade-dst

  Source code for transferable dialogue state generator (TRADE, Wu et al., 2019). https://arxiv.org/abs/1905.08743

  Language:Python3912238115

• Alex-Fabbri/Multi-News

  Large-scale multi-document summarization dataset and code

  Language:Python27233653

• BangLiu/ArticlePairMatching

  The code of ACL 2019 paper: Matching Article Pairs with Graphical Decomposition and Convolutions

  Language:Python23573960

• woshiyyya/DFGN-pytorch

  Code for ACL19 paper: Dynamically Fused Graph Network for Multihop Reasoning

  Language:Python190103142

• allenai/vampire

  Variational Methods for Pretraining in Resource-limited Environments

  Language:Python174113133

• wenhuchen/HDSA-Dialog

  Code and Data for ACL 2019 "Semantically Conditioned Dialog Response Generation via Hierarchical Disentangled Self-Attention"

  Language:Python13691139

• henryhungle/MTN

  Code for the paper Multimodal Transformer Networks for End-to-End Video-Grounded Dialogue Systems (ACL19)

  Language:Python9861325

• martiansideofthemoon/squash-generation

  Official code and data repository for our ACL 2019 long paper "Generating Question-Answer Hierarchies" (https://arxiv.org/abs/1906.02622).

  Language:Python9563530

• Yifan-Gao/conversational-QG

  [ACL 2019]: Interconnected Question Generation with Coreference Alignment and Conversation Flow Modeling

  Language:Python886621

• bernhard2202/rankqa

  This is the PyTorch implementation of the ACL 2019 paper RankQA: Neural Question Answering with Answer Re-Ranking.

  Language:Python8410416

• facebookresearch/TreeNLG

  A novel method of constrained decoding for neural NLG (NNLG) models

  Language:Python84131018

• dojoteef/synst

  Source code to reproduce the results in the ACL 2019 paper "Syntactically Supervised Transformers for Faster Neural Machine Translation"

  Language:Python82576

• mingdachen/syntactic-template-generation

  Code for "Controllable Paraphrase Generation with a Syntactic Exemplar" (ACL 2019)

  Language:Python79247

• ratishsp/data2text-entity-py

  Code for ACL 2019 paper on Data-to-text Generation with Entity Modeling

  Language:Python744617

• airsplay/VisualRelationships

  Data of ACL 2019 Paper "Expressing Visual Relationships via Language".

  Language:Jupyter Notebook62827

• shmsw25/single-hop-rc

  An original implementation of ACL 2019, "Compositional Questions Do Not Necessitate Multi-hop Reasoning" (Single-hop Reading Comprehension Model based on BERT)

  Language:Python58447

• Linear95/BinarySentEmb

  Code for ACL 2019 oral paper - Learning Compressed Sentence Representations for On-Device Text Processing.

  Language:Python44637

• lisa-sicuan/dlcl

  The implementation of "Learning Deep Transformer Models for Machine Translation"

  Language:Python1000

• lisa-sicuan/pytorch_graph-rel

  A PyTorch implementation of GraphRel

  Language:Jupyter Notebook1000

• lisa-sicuan/stog

  AMR Parsing as Sequence-to-Graph Transduction

  Language:Python1000