Kung-Hsiang Steeve Huang (khuangaf)

khuangaf

Geek Repo

Location:Champaign, Illinois

Home Page:http://khuangaf.github.io/

Twitter:@steeve__huang

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Kung-Hsiang Steeve Huang 's repositories

CryptocurrencyPrediction

Predict Cryptocurrency Price with Deep Learning

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PyTorch-Geometric-YooChoose

This is a tutorial for PyTorch Geometric on the YooChoose dataset

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Awesome-Chart-Understanding

A curated list of recent and past chart understanding work based on our survey paper: From Pixels to Insights: A Survey on Automatic Chart Understanding in the Era of Large Foundation Models.

FakingFakeNews

Official implementation of the ACL 2023 paper: "Faking Fake News for Real Fake News Detection: Propaganda-Loaded Training Data Generation"

CHOCOLATE

Code and data for the paper "Do LVLMs Understand Charts? Analyzing and Correcting Factual Errors in Chart Captioning"

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ZeroFEC

Official implementation of the ACL 2023 paper: "Zero-shot Faithful Factual Error Correction"

tibame_recommender_system

TibaMe 「打造智能推薦系統:用AI搞懂客戶精準行銷」 實作課程程式碼

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CONCRETE

Official implementation of "CONCRETE: Improving Cross-lingual Fact Checking with Cross-lingual Retrieval" (COLING'22)

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DeepCTR

Easy-to-use,Modular and Extendible package of deep-learning based CTR models.

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dygie-doc

DyGIE-Doc: An End-to-end Document-level Relation Extraction System

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genia-tagger-py

Python wrapper for GENIA tagger

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gtt

Template Filling with Generative Transformers

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hugo-academic

📝 The website builder for Hugo. Build and deploy a beautiful website in minutes!

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KagNet

Knowledge-Aware Graph Networks for Commonsense Reasoning (EMNLP-IJCNLP 19)

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planning_dial_summ

One implementation of the paper "Controllable Neural Dialogue Summarization with Personal Named Entity Planning".

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Pytorch-NCE

The Noise Contrastive Estimation for softmax output written in Pytorch

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SciREX

Data/Code Repository for https://api.semanticscholar.org/CorpusID:218470122

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timeseries-tutorial-kdd-2022

Github source for KDD'22 Time Series Tutorial website

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transformers

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

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