sonlam1102

sonlam1102's Stars

• acl-org/acl-anthology

  Data and software for building the ACL Anthology.

  Language:Python432202.3k290

• RUCAIBox/HaluEval

  This is the repository of HaluEval, a large-scale hallucination evaluation benchmark for Large Language Models.

  Language:Python40991225

• binhvq/news-corpus

  Corpus tiếng việt

  346101070

• google-deepmind/AQuA

  A algebraic word problem dataset, with multiple choice questions annotated with rationales.

  29722144

• jindongwang/Pytorch-CapsuleNet

  An easy-to-follow Pytorch implementation of Hinton's Capsule Network

  Language:Python19041857

• jerbarnes/semeval22_structured_sentiment

  SemEval-2022 Shared Task 10: Structured Sentiment Analysis

  Language:Python75113042

• jerbarnes/sentiment_graphs

  Graph parsing approach to structured sentiment analysis.

  Language:Python40386

• VT-NLP/Mocheg

  Dataset and Code for Multimodal Fact Checking and Explanation Generation (Mocheg)

  Language:Python403138

• phusroyal/ViHOS

  Repository for the paper "ViHOS: Vietnamese Hate and Offensive Spans Detection" (EACL2023)

  Language:Jupyter Notebook332010

• CSHaitao/THUIR-COLIEE2023

  Code to reproduce THUIR‘s submissions for COLIEE 2023 Task1 and Task2

  Language:Python23111

• bino282/ViNLP

  Language:Python17415

• ds4v/absa-vlsp-2018

  End-to-end Multi-task Solutions for Aspect Category Sentiment Analysis (ACSA) on Vietnamese Datasets

  Language:Jupyter Notebook17104

• kh4nh12/llm_learning_resource

  Large Language Models (LLMs) Learning Resources

  16101

• seoneun/T5-Question-Generation

  SQuAD Question Generation module based on T5-large

  Language:Python16201

• heraclex12/vietpunc

  Vietnamese Punctuation Prediction using Pretrained Language Models

  Language:Jupyter Notebook13216

• mrzjy/sunburst

  A simple Python implementation of ngram sunburst (nested pie chart) visualization showed in CoQA paper

  Language:Python13114

• kh4nh12/ViVQA

  12121

• LuongPhan/UIT-ViSFD

  12112

• cyoon47/CS1QA

  Repository for CS1QA: A Dataset for assisting Code-based Question Answering in an Introductory Programming Course, published at NAACL 2022

  Language:Python11211

• kietnv/vireader

  Machine Reading Comprehension has attracted significant interest in research on natural language understanding, and large-scale datasets and neural network-based methods have been developed for this task. However, most developments of resources and methods in machine reading comprehension have been investigated using two resource-rich languages, English and Chinese. This article proposes a system called ViReader for open-domain machine reading comprehension in Vietnamese by using Wikipedia as the textual knowledge source, where the answer to any particular question is a textual span derived directly from texts on Vietnamese Wikipedia. Our system combines a sentence retriever component, based on techniques of information retrieval to extract the relevant sentences, with a transfer learning-based answer extractor trained to predict answers based on Wikipedia texts. Experiments on multiple datasets for machine reading comprehension in Vietnamese and other languages demonstrate that (1) our ViReader system is highly competitive with prevalent machine learning-based systems, and (2) multi-task learning by using a combination consisting of the sentence retriever and answer extractor is an end-to-end reading comprehension system. The sentence retriever component of our proposed system retrieves the sentences that are most likely to provide the answer response to the given question. The transfer learning-based answer extractor then reads the document from which the sentences have been retrieved, predicts the answer, and returns it to the user. The ViReader system achieves new state-of-the-art performances, with values of 70.83% EM (exact match) and 89.54% F1, outperforming the BERT-based system by 11.55% and 9.54%, respectively. It also obtains state-of-the-art performance on UIT-ViNewsQA (another Vietnamese dataset consisting of online health-domain news) and BiPaR (a bilingual dataset on English and Chinese novel texts). Compared with the BERT-based system, our system achieves significant improvements (in terms of F1) with 7.65% for English and 6.13% for Chinese on the BiPaR dataset. Furthermore, we build a ViReader application programming interface that programmers can employ in Artificial Intelligence applications.

  Language:Jupyter Notebook10111

• barshana-banerjee/ParaQA

  A Dataset with Multiple Paraphrase Responses for Single-Turn Question Answering

  9212

• ngxtnhi/ViLexNorm

  A Lexical Normalization Corpus for Vietnamese Social Media Text

  8110

• vuraemon/UITws-v1

  [PACLING 2019] Vietnamese Word Segmentation with SVM: Ambiguity Reduction and Suffix Capture

  Language:Jupyter Notebook6401

• kh4nh12/UIT-ViON-Dataset

  An Open-domain, Large-scale and High-quality Dataset of Online News in Vietnamese

  4100

• AnhHoang0529/Small-LexNormViHSD

  A Dataset for Vietnamese Lexical Normalization

  3101

• JkUndead/UIT-ViNames-Dataset

  UIT-ViNames is a dataset for Predicting Genders for Vietnamese Names

  3201

• DoPhamPhucTinh/ViRe4MRC

  ViRe4MRC is the first benchmark for review-based machine reading comprehension in Vietnamese. ViRe4MRC contains 6,603 data points, human-generated from 2,174 reviews on two domains: restaurant and smartphone.

  2122

• arghadeep25/Database

  Geodatabase using Postgre SQL

  1000

• Khoacannotcode/VinAI_2020

  VinBigData Chest X-ray Abnormalities Detection

  Language:Python110

• mlip-cmu/mlip-cmu.github.io

  Homepage

  Language:HTML1000