TinaBBB

TinaBBB's Stars

• CSSLab/social-dimensions

  Data and code accompanying the Nature paper "Quantifying social organization and political polarization in online platforms"

  Language:Jupyter Notebook6016

• DarrenZhang01/ExCon

  ExCon: Explanation-driven Supervised Contrastive Learning

  Language:Python18

• facebookresearch/faiss

  A library for efficient similarity search and clustering of dense vectors.

  Language:C++32.3k3.7k

• deepeshhada/ReXPlug

  ReXPlug: Explainable Recommendation using Plug and Play Language Model, SIGIR 2021

  Language:Python104

• microsoft/SpeedyRec

  Language:Python245

• alexwolson/yelpscraper

  Language:Python1

• chaitjo/personalized-dialog

  Code for the paper 'Personalization in Goal-oriented Dialog' (NeurIPS 2017 Conversational AI Workshop)

  Language:Python13345

• princeton-nlp/SimCSE

  [EMNLP 2021] SimCSE: Simple Contrastive Learning of Sentence Embeddings https://arxiv.org/abs/2104.08821

  Language:Python3.5k519

• mabdullah1994/Text-Classification-with-BERT-PyTorch

  A text classifier fine tuned on pre-trained BERT for Sarcasm Detection in News Headlines (PyTorch Implementation)

  Language:Python377

• Guzpenha/ConvRecProbingBERT

  Code for the paper "What does BERT know about books, movies and music? Probing BERT for Conversational Recommendation" at RecSys'20

  Language:Python237

• THUDM/KBRD

  Towards Knowledge-Based Recommender Dialog System @ EMNLP 2019

  Language:Python13432

• facebookresearch/ParlAI

  A framework for training and evaluating AI models on a variety of openly available dialogue datasets.

  Language:Python10.5k2.1k

• ReDialData/website

  366

• VectorInstitute/projectpensive

  Language:Jupyter Notebook33

• google-research/google-research

  Google Research

  Language:Jupyter Notebook34.6k8k

• google-research-datasets/ccpe

  A dataset consisting of 502 English dialogs with 12,000 annotated utterances between a user and an assistant discussing movie preferences in natural language. It was collected using a Wizard-of-Oz methodology between two paid crowd-workers, where one worker plays the role of an 'assistant', while the other plays the role of a 'user'. The 'assistant' elicits the 'user’s' preferences about movies following a Coached Conversational Preference Elicitation (CCPE) method. The assistant asks questions designed to minimize the bias in the terminology the 'user' employs to convey his or her preferences as much as possible, and to obtain these preferences in natural language. Each dialog is annotated with entity mentions, preferences expressed about entities, descriptions of entities provided, and other statements of entities.

  254

• google-research-datasets/soft-attributes

  This dataset consists of sets of movie titles, with each set annotated with a single English soft attribute (such as 'confusing' or 'romantic') and a reference movie. For each set, a rater has placed the movies into three sets: more, equally, and less <attribute> than the reference movie. From these sets, approximately 250,000 pairwise preferences can be derived for 60 distinct soft attributes studied.

  73

• yoongi0428/RecSys_PyTorch

  PyTorch implementations of Top-N recommendation, collaborative filtering recommenders.

  Language:Python14021

• shubhamjha97/hierarchical-clustering

  A Python implementation of divisive and hierarchical clustering algorithms. The algorithms were tested on the Human Gene DNA Sequence dataset and dendrograms were plotted.

  Language:Python8231

• scikit-learn/scikit-learn

  scikit-learn: machine learning in Python

  Language:Python60.7k25.5k

• Darkprogrammerpb/DeepLearningProjects_when_I_was_a_noob

  Language:Jupyter Notebook2736

• wuga214/DeepCritiquingForRecSys

  Official Code Framework of the paper "Deep Language-based Critiquing for Recommender System"

  Language:Jupyter Notebook193

• ficstamas/word_embedding_interpretability

  Language:Python2

• facebookresearch/barlowtwins

  PyTorch implementation of Barlow Twins.

  Language:Python966127

• abidlabs/contrastive_vae

  Contrastive Variational Autoencoders

  Language:Jupyter Notebook628

• HobbitLong/SupContrast

  PyTorch implementation of "Supervised Contrastive Learning" (and SimCLR incidentally)

  Language:Python3.2k538

• THUwangcy/ReChorus

  “Chorus” of recommendation models: a light and flexible PyTorch framework for Top-K recommendation.

  Language:Python56597

• sthalles/SimCLR

  PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations

  Language:Jupyter Notebook2.3k467

• GuanZhengChen/CAN-Pytorch

  Language:Python32

• mengzaiqiao/CAN

  Co-embedding Attributed Networks

  Language:Python6421