This repository provides an insight into ventures of framing an intelligent Command line interface (CLI) for UNIX Based Systems.

Code-Switching Language Modeling using Syntax-Aware Multi-Task Learning (CALCS 2018, ACL)

Python project planing organizer for python formation Adep Roubaix

Source code and datasets for EMNLP 2019 paper: Jointly Learning Entity and Relation Representations for Entity Alignment.

Joint text classification on multiple levels with multiple labels, using a multi-head attention mechanism to wire two prediction tasks together.

This project allows users to add, delete and views information of all their employees.

2021 CCF BDCI 全国信息检索挑战杯（CCIR-Cup）智能人机交互自然语言理解赛道第二名参赛解决方案

PyTorch code for JEREX: Joint Entity-Level Relation Extractor

Our source code for the paper "Transformer-based Joint Learning Approach for Text Normalization in Vietnamese ASR"

Streamlit web app of covid-forecasting-joint-learning

COVID-19 forecasting model for East Java cities using Joint Learning. My undergrad thesis.

Implementation of PAKDD'20 paper: "Jointly Modelling Attribute Interactions and Relationships for Cross-lingual Knowledge Alignment".

Opinion recommendation is a task, recently introduced, for consistently generating a text review and a rating score that a certain user would give to a certain product, which has never seen before. Input information driving recommendation is text reviews and ratings for this product contributed by other users and text reviews submitted by the us…

Implementation of joint construction of Mask/BBox heads in QDTrack-mots for joint training research

A part-of-speech/morphological tagger and a dependency parser that can be trained separately or jointly, with special methods for Ancient Greek.

PyTorch code for SpERT: Span-based Entity and Relation Transformer

Multi-target Random Forest implementation that can mix both classification and regression tasks.

Official PyTorch implementation of the paper "Joint Learning of Blind Super-Resolution and Crack Segmentation for Realistic Degraded Images", IEEE Transactions on Instrumentation and Measurement (TIM) 2024. CSBSR is an advanced version of our previous work CSSR [MVA'21].

Crack Segmentation for Low-Resolution Images using Joint Learning with Super-Resolution (CSSR) was accepted to international conference on MVA2021 (oral), and selected for the Best Practical Paper Award.