Publications

Understanding the User: An Intent-Based Ranking Dataset

Abhijit Anand, Jurek Leonhardt, Venktesh V, Avishek Anand
Resource paper (CIKM 2024)
ACM | arXiv | code

Data Augmentation for Sample Efficient and Robust Document Ranking

Abhijit Anand, Jurek Leonhardt, Jaspreet Singh, Koustav Rudra, Avishek Anand
Journal paper (TOIS 2024)
ACM | arXiv

Efficient Neural Ranking using Forward Indexes and Lightweight Encoders

Jurek Leonhardt, Henrik Müller, Koustav Rudra, Megha Khosla, Abhijit Anand, Avishek Anand
Journal paper (TOIS 2024)
ACM | arXiv | slides | code

Efficient and Explainable Neural Ranking

Jurek Leonhardt
PhD thesis (2023)
TIB | slides

Extractive Explanations for Interpretable Text Ranking

Jurek Leonhardt, Koustav Rudra, Avishek Anand
Journal paper (TOIS 2023)
ACM | arXiv | slides | code

Supervised Contrastive Learning Approach for Contextual Ranking

Abhijit Anand, Jurek Leonhardt, Koustav Rudra, Avishek Anand
Full paper (ICTIR 2022)
ACM | arXiv | slides

Efficient Neural Ranking using Forward Indexes

Jurek Leonhardt, Koustav Rudra, Megha Khosla, Abhijit Anand, Avishek Anand
Full paper (TheWebConf 2022)
ACM | arXiv | slides | code

Exploiting Sentence-Level Representations for Passage Ranking

Jurek Leonhardt, Fabian Beringer, Avishek Anand
Workshop paper (LWDA 2021)
CEUR | arXiv | slides | code

Boilerplate Removal using a Neural Sequence Labeling Model

Jurek Leonhardt, Avishek Anand, Megha Khosla
Demo paper (TheWebConf 2020)
ACM | arXiv | slides | code

Node Representation Learning for Directed Graphs

Megha Khosla, Jurek Leonhardt, Wolfgang Nejdl, Avishek Anand
Full paper (ECML-PKDD 2019)
Springer | arXiv

User Fairness in Recommender Systems

Jurek Leonhardt, Avishek Anand, Megha Khosla
Short paper (TheWebConf 2018)
ACM | arXiv