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Name: Sebastian Hofstätter
Type: User
Company: Cohere
Bio: Teaching LLMs about relevance @cohere-ai PhD in efficient neural information retrieval from TU Vienna
Twitter: s_hofstaetter
Name: Sebastian Hofstätter
Type: User
Company: Cohere
Bio: Teaching LLMs about relevance @cohere-ai PhD in efficient neural information retrieval from TU Vienna
Twitter: s_hofstaetter
A toolkit for reproducible information retrieval research built on Lucene
Api and library for getting related terms from a word embedding
Fine-Grained Relevance Annotations for Multi-Task Document Ranking and Question Answering
A TypeScript pre-processor for AngularJS
Generalized Translation Models in the Probabilistic Relevance Framework implemented in Lucene & Solr
Training & evaluation library for text-based neural re-ranking and dense retrieval models built with PyTorch
Neural-IR-Explorer: A Content-Focused Tool to Explore Neural Re-Ranking Results
Implementation and Evaluation of "A Deep Relevance Matching Model for Ad-hoc Retrieval"
Improving Efficient Neural Ranking Models with Cross-Architecture Knowledge Distillation
Prototype of a super-fast search engine for information retrieval tasks using .NET Core
Source code for: On the Effect of Low-Frequency Terms on Neural-IR Models, SIGIR'19
SIGIR 2021: Efficiently Teaching an Effective Dense Retriever with Balanced Topic Aware Sampling
Open-Source Information Retrieval Courses @ TU Wien
Establishing Strong Baselines for TripClick Health Retrieval; ECIR 2022
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