sebastian-hofstaetter/neural-ir-explorer

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Created over 6 years ago
Updated almost 5 years ago

sebastian-hofstaetter/neural-ir-explorer

sebastian-hofstaetter

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Neural-IR-Explorer: A Content-Focused Tool to Explore Neural Re-Ranking Results

teaching

Open-Source Information Retrieval Courses @ TU Wien

matchmaker

Training & evaluation library for text-based neural re-ranking and dense retrieval models built with PyTorch

neural-ranking-kd

Improving Efficient Neural Ranking Models with Cross-Architecture Knowledge Distillation

Jupyter Notebook

tas-balanced-dense-retrieval

SIGIR 2021: Efficiently Teaching an Effective Dense Retriever with Balanced Topic Aware Sampling

Jupyter Notebook

sigir19-neural-ir

Source code for: On the Effect of Low-Frequency Terms on Neural-IR Models, SIGIR'19

colberter

Jupyter Notebook

neural-ranking-drmm

Implementation and Evaluation of "A Deep Relevance Matching Model for Ad-hoc Retrieval"

intra-document-cascade

Jupyter Notebook

ir-generalized-translation-models

Generalized Translation Models in the Probabilistic Relevance Framework implemented in Lucene & Solr

fira-trec-19-dataset

Fine-Grained Relevance Annotations for Multi-Task Document Ranking and Question Answering

search-engine

Prototype of a super-fast search engine for information retrieval tasks using .NET Core

tripclick

Establishing Strong Baselines for TripClick Health Retrieval; ECIR 2022

embedding_vector_similarity

Api and library for getting related terms from a word embedding