Pinned Repositories
CHIME
[COLING20] CHIME: Cross-passage Hierarchical Memory Network for Generative Review Question Answering
LLM_Finetune
SFT, DPO and Inference scripts for LLM
MemoChat
MemoChat: Tuning LLMs to Use Memos for Consistent Long-Range Open-Domain Conversation
My_QA_Robot
An AutoQA chatbot based on historical QA pairs and realized through local KB & online crawler
NapSS
[EACL23] NapSS: Paragraph-level Medical Text Simplification via Narrative Prompting and Sentence-matching Summarization
SamPO
[EMNLP24] Eliminating Biased Length Reliance of Direct Preference Optimization via Down-Sampled KL Divergence
Sentences_Pair_Similarity_Calculation_Siamese_LSTM
A Keras Implementation of Attention_based Siamese Manhattan LSTM
SentenceSimilarityMatching
Sentence Similarity Matching based on TextCNN and N-gram Feature Map
SMPCUP2017_ELP
6th Place Solution for SMP CUP 2017 (Third Prize)
weibo_analyst
这是一个微博评论分析工具,实现功能主要有:1.微博评论数据爬取;2.分词与关键词提取;3.词云与词频统计;4.情感分析;5.主题聚类
LuJunru's Repositories
LuJunru/MemoChat
MemoChat: Tuning LLMs to Use Memos for Consistent Long-Range Open-Domain Conversation
LuJunru/SMPCUP2017_ELP
6th Place Solution for SMP CUP 2017 (Third Prize)
LuJunru/SamPO
[EMNLP24] Eliminating Biased Length Reliance of Direct Preference Optimization via Down-Sampled KL Divergence
LuJunru/LLM_Finetune
SFT, DPO and Inference scripts for LLM
LuJunru/NapSS
[EACL23] NapSS: Paragraph-level Medical Text Simplification via Narrative Prompting and Sentence-matching Summarization
LuJunru/CHIME
[COLING20] CHIME: Cross-passage Hierarchical Memory Network for Generative Review Question Answering
LuJunru/FIPO_Project
[COLING25] Free-form Instruction-oriented Prompt Optimization with Preference Dataset and Modular Fine-tuning Schema
LuJunru/funNLP
中英文敏感词、语言检测、中外手机/电话归属地/运营商查询、名字推断性别、手机号抽取、身份证抽取、邮箱抽取、中日文人名库、中文缩写库、拆字词典、词汇情感值、停用词、反动词表、暴恐词表、繁简体转换、英文模拟中文发音、汪峰歌词生成器、职业名称词库、同义词库、反义词库、否定词库、汽车品牌词库、汽车零件词库、连续英文切割、各种中文词向量、公司名字大全、古诗词库、IT词库、财经词库、成语词库、地名词库、历史名人词库、诗词词库、医学词库、饮食词库、法律词库、汽车词库、动物词库、中文聊天语料、中文谣言数据、百度中文问答数据集、句子相似度匹配算法集合、bert资源、文本生成&摘要相关工具、cocoNLP信息抽取工具
LuJunru/TranCLR
[EMNLP22] Event-Centric Question Answering via Contrastive Learning and Invertible Event Transformation
LuJunru/ADS2018_Final_Project
This is our final project for CUSP 2018 Fall ADS Final Project
LuJunru/Algorithm_Interview_Notes-Chinese
2018/2019/校招/春招/秋招/算法/机器学习(Machine Learning)/深度学习(Deep Learning)/自然语言处理(NLP)/C/C++/Python/面试笔记
LuJunru/BDM_lj1230
A space for 2019 Spring Big Data Management Course
LuJunru/CS-Notes
:books: 技术面试必备基础知识、Leetcode 题解、后端面试、Java 面试、春招、秋招、操作系统、计算机网络、系统设计
LuJunru/CUSL
NYU CUSP Pre-fall online course
LuJunru/DeepLearning-500-questions
深度学习500问,以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述,以帮助自己及有需要的读者。 全书分为18个章节,50余万字。由于水平有限,书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作,联系scutjy2015@163.com 版权所有,违权必究 Tan 2018.06
LuJunru/EventQAviaPR
LuJunru/fairseq
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
LuJunru/LuJunru.github.io
personal blog
LuJunru/MLC2019_Final_Project
This is our final project for CUSP 2019 Spring MLC Final Project
LuJunru/NeroParser
⚡️ 20,000/ms Parser NLP POS AI Chinese words from complex sentence /每秒高达2700万混合分词, 高精准确率,支持病句分析,词性,词频统计,自由扩充词库的快速神经网络中文分词包.
LuJunru/NYCData
Some NYC data
LuJunru/NYU-CUSP-Capstone-2019
Capstone Project of NYU CUSP 2019: DOES UBER/LYFT REDUCE PARKING VIOLATIONS IN NEW YORK CITY?
LuJunru/PUI2018_fb55
homework assignments and solutions for CUSP PUI 2018 https://serv.cusp.nyu.edu/~fbianco/PUI2018
LuJunru/pyserini
Pyserini is a Python toolkit for reproducible information retrieval research with sparse and dense representations.
LuJunru/Python
All Algorithms implemented in Python
LuJunru/python_interview_question
关于python的面试题
LuJunru/pytorch-pretrained-BERT
A PyTorch implementation of Google AI's BERT model provided with Google's pre-trained models, examples and utilities.
LuJunru/pytorch-sentiment-analysis
Tutorials on getting started with PyTorch and TorchText for sentiment analysis.
LuJunru/SentimentAnalysisUIR
Sentiment Analysis System - UIR
LuJunru/SmallPieces-Python
Some small daily accumulations on Python