SeonjeongHwang

SeonjeongHwang's Stars

• tensorflow/models

  Models and examples built with TensorFlow

  Language:Python76.9k2.7k7.3k45.8k

• facebookresearch/fairseq

  Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

  Language:Python30.1k4284.2k6.4k

• zihangdai/xlnet

  XLNet: Generalized Autoregressive Pretraining for Language Understanding

  Language:Python6.2k1702631.2k

• Diego999/pyGAT

  Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)

  Language:Python2.9k1771687

• gordicaleksa/pytorch-GAT

  My implementation of the original GAT paper (Veličković et al.). I've additionally included the playground.py file for visualizing the Cora dataset, GAT embeddings, an attention mechanism, and entropy histograms. I've supported both Cora (transductive) and PPI (inductive) examples!

  Language:Jupyter Notebook2.4k4614322

• google-research/electra

  ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators

  Language:Python2.3k60123351

• jungwoo-ha/WeeklyArxivTalk

  [Zoom & Facebook Live] Weekly AI Arxiv 시즌2

  9711959341

• teacherpeterpan/Question-Generation-Paper-List

  A summary of must-read papers for Neural Question Generation (NQG)

  58328679

• cooelf/AwesomeMRC

  IJCAI 2021 Tutorial & code for Retrospective Reader for Machine Reading Comprehension (AAAI 2021)

  Language:Python36193067

• mahnazkoupaee/WikiHow-Dataset

  A Large Scale Text Summarization Dataset

  Language:Python32882241

• hsinyuan-huang/FlowQA

  Implementation of conversational QA model: FlowQA (with slight improvement)

  Language:Python19892657

• AIRC-KETI/ke-t5

  Language:Python19121618

• monologg/DistilKoBERT

  Distillation of KoBERT from SKTBrain (Lightweight KoBERT)

  Language:Python1856825

• prdwb/bert_hae

  BERT with History Answer Embedding for Conversational Question Answering

  Language:Python1157823

• Yifan-Gao/conversational-QG

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

  Language:Python886621

• ecchochan/roberta-squad

  roBERTa training for SQuAD

  Language:Python513118

• MrBananaHuman/KalBert

  Korean ALBERT

  Language:Python47235

• sh0416/clrcmd

  Official Repository for CLRCMD (Appear in ACL2022)

  Language:Jupyter Notebook38264

• hugochan/GraphFlow

  Code & data accompanying the IJCAI 2020 paper "GraphFlow: Exploiting Conversation Flow with Graph Neural Networks for Conversational Machine Comprehension"

  Language:Python352212

• dmis-lab/excord

  Learn to Resolve Conversational Dependency: A Consistency Training Framework for Conversational Question Answering (Kim et al., ACL 2021)

  Language:Python31482

• asahi417/lm-vocab-trimmer

  Vocabulary Trimming (VT) is a model compression technique, which reduces a multilingual LM vocabulary to a target language by deleting irrelevant tokens from its vocabulary. This repository contains a python-library vocabtrimmer, that remove irrelevant tokens from a multilingual LM vocabulary for the target language.

  Language:Python28231

• sion-zcfei/CQG

  The codes for ACL2022 paper “CQG: A Simple and Effective Controlled Generation Framework for Multi-hop Question Generation

  Language:Python23169

• lyeoni/pytorch-mnist-CVAE

  Language:Jupyter Notebook21108

• cwnu-airlab/Fact-Reasoning-POSTECH

  Language:Python20102

• xiajing10/akec

  Unsupervised Key-phrase Extraction and Clustering for Classification Scheme in Scientific Publications.

  Language:Jupyter Notebook19422

• Orange-OpenSource/COQAR

  a corpus containing 4.5K conversations from the Conversational Question-Answering dataset CoQA, for a total of 53K follow-up question-answer pairs, in which each original question was manually annotated with at least 2 and at most 3 out-of-context rewritings

  Language:Python161116

• ncbi-nlp/ezTag

  Web interface that allows users to perform computer-assisted text annotation

  Language:JavaScript15356

• MehwishFatimah/GPT2_Summarization

  Finetune GPT2 for text summarization

  Language:Python13213

• searchableai/ChainCQG

  Language:Python12465

• LZKSKY/CaSE_RISE

  This is the implementation of paper "Learning to Ask Conversational Questions by Optimizing Levenshtein Distance".

  Language:Python9204