jingtaozhan

DRhard

SIGIR'21: Optimizing DR with hard negatives and achieving SOTA first-stage retrieval performance on TREC DL Track.

RepCONC

WSDM'22 Best Paper: Learning Discrete Representations via Constrained Clustering for Effective and Efficient Dense Retrieval

RepBERT-Index

RepBERT is a competitive first-stage retrieval technique. It represents documents and queries with fixed-length contextualized embeddings. The inner products of them are regarded as relevance scores. Its efficiency is comparable to bag-of-words methods.

disentangled-retriever

An easy-to-use python toolkit for flexibly adapting various neural ranking models to any target domain.

JPQ

CIKM'21: JPQ substantially improves the efficiency of Dense Retrieval with 30x compression ratio, 10x CPU speedup and 2x GPU speedup.

bert-ranking-analysis

SIGIR'20: An Analysis of BERT in Document Ranking

extrapolate-eval

CIKM 2022: Evaluating Interpolation and Extrapolation Performance of Neural Retrieval Models

PromptReformulate

pyserini

Pyserini is a Python toolkit for reproducible information retrieval research with sparse and dense representations.

BERT-related-papers

BERT-related papers

DL4EEG-Classification

The implementation of deep learning models for EEG classification.

DRScale

guide

The Student's Guide to @lintool

jingtaozhan

jingtaozhan.github.io

Homepage

Rayuela.jl

Code for my PhD thesis. Library of quantization-based methods for fast similarity search in high dimensions. Presented at ECCV 18.

warc-clueweb

Python library for reading ClueWeb09's warc files