Git Product home page Git Product logo

Hi there 👋

DreamInvoker

This is Shuang Zeng [google scholar].

Currently, I am an Algorithm Engineer in Data-Douyin-Comment at ByteDance.

I got my Master's Degree at Peking University under the supervision of Prof. Baobao Chang [google scholar].

My research interests now include Large Vision-Language Model (LVLM), Retrieval-augmented Generation (RAG), Text2SQL, and Question Answering (QA). My previous research interests include Graph Neural Networks (GNNs), Information Extraction (IE), and knowledge graphs (KGs).

Profile Summary

summary

Shuang Zeng's Projects

aggcn_tacred icon aggcn_tacred

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

alicoco icon alicoco

Alibaba E-commerce Cognitive Concept Net

auto-gpt icon auto-gpt

An experimental open-source attempt to make GPT-4 fully autonomous.

cfer-document-level-re icon cfer-document-level-re

Code and data for the paper: Coarse-to-Fine Entity Representations for Document-level Relation Extraction

cookiecutter icon cookiecutter

A cross-platform command-line utility that creates projects from cookiecutters (project templates), e.g. Python package projects, C projects.

coref-hgat icon coref-hgat

Pytorch Implementation of Our NAACL 2021 Paper "Incorporating Syntax and Semantics in Coreference Resolution with Heterogeneous Graph Attention Network"

coref-hoi icon coref-hoi

PyTorch implementation of the end-to-end coreference resolution model with different higher-order inference methods.

dcgcn icon dcgcn

Densely Connected Graph Convolutional Networks for Graph-to-Sequence Learning (authors' MXNet implementation for the TACL19 paper)

detr icon detr

End-to-End Object Detection with Transformers

doccano icon doccano

Open source text annotation tool for machine learning practitioner.

encattagg icon encattagg

Codes for ICKG 2020 paper "Improving Document-level Relation Extraction via Contextualizing Mention Representations and Weighting Mention Pairs"

explore-and-evaluate icon explore-and-evaluate

Code for EMNLP2020 paper "Exploring and Evaluating Attributes, Values, and Structures for Entity Alignment".

gain icon gain

Source code for EMNLP 2020 paper: Double Graph Based Reasoning for Document-level Relation Extraction

glre icon glre

Global-to-Local Neural Networks for Document-Level Relation Extraction, EMNLP 2020

gritlm icon gritlm

Generative Representational Instruction Tuning

ie_paper_notes icon ie_paper_notes

Paper notes for Information Extraction, including Relation Extraction (RE), Named Entity Recognition (NER), Entity Linking (EL), Event Extraction (EE), Named Entity Disambiguation (NED).

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.