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09/12/2023
Annotating Data for Fine-Tuning a Neural Ranker? Current Active Learning Strategies are not Better than Random Selection
Search methods based on Pretrained Language Models (PLM) have demonstrat...
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05/24/2023
Ranger: A Toolkit for Effect-Size Based Multi-Task Evaluation
In this paper, we introduce Ranger - a toolkit to facilitate the easy us...
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09/28/2022
FiD-Light: Efficient and Effective Retrieval-Augmented Text Generation
Retrieval-augmented generation models offer many benefits over standalon...
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08/14/2022
TripJudge: A Relevance Judgement Test Collection for TripClick Health Retrieval
Robust test collections are crucial for Information Retrieval research. ...
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07/07/2022
Multi-Task Retrieval-Augmented Text Generation with Relevance Sampling
This paper studies multi-task training of retrieval-augmented generation...
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06/26/2022
Are We There Yet? A Decision Framework for Replacing Term Based Retrieval with Dense Retrieval Systems
Recently, several dense retrieval (DR) models have demonstrated competit...
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03/24/2022
Introducing Neural Bag of Whole-Words with ColBERTer: Contextualized Late Interactions using Enhanced Reduction
Recent progress in neural information retrieval has demonstrated large g...
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01/05/2022
PARM: A Paragraph Aggregation Retrieval Model for Dense Document-to-Document Retrieval
Dense passage retrieval (DPR) models show great effectiveness gains in f...
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01/02/2022
Establishing Strong Baselines for TripClick Health Retrieval
We present strong Transformer-based re-ranking and dense retrieval basel...
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10/11/2021
A Time-Optimized Content Creation Workflow for Remote Teaching
We describe our workflow to create an engaging remote learning experienc...
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06/10/2021
Linguistically Informed Masking for Representation Learning in the Patent Domain
Domain-specific contextualized language models have demonstrated substan...
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05/20/2021
Intra-Document Cascading: Learning to Select Passages for Neural Document Ranking
An emerging recipe for achieving state-of-the-art effectiveness in neura...
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04/19/2021
Improving Transformer-Kernel Ranking Model Using Conformer and Query Term Independence
The Transformer-Kernel (TK) model has demonstrated strong reranking perf...
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04/14/2021
Efficiently Teaching an Effective Dense Retriever with Balanced Topic Aware Sampling
A vital step towards the widespread adoption of neural retrieval models ...
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01/18/2021
Mitigating the Position Bias of Transformer Models in Passage Re-Ranking
Supervised machine learning models and their evaluation strongly depends...
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12/21/2020
Cross-domain Retrieval in the Legal and Patent Domains: a Reproducibility Study
Domain specific search has always been a challenging information retriev...
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11/14/2020
Conformer-Kernel with Query Term Independence at TREC 2020 Deep Learning Track
We benchmark Conformer-Kernel models under the strict blind evaluation s...
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10/06/2020
Improving Efficient Neural Ranking Models with Cross-Architecture Knowledge Distillation
The latency of neural ranking models at query time is largely dependent ...
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08/12/2020
Fine-Grained Relevance Annotations for Multi-Task Document Ranking and Question Answering
There are many existing retrieval and question answering datasets. Howev...
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07/20/2020
Conformer-Kernel with Query Term Independence for Document Retrieval
The Transformer-Kernel (TK) model has demonstrated strong reranking perf...
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05/17/2020
DEXA: Supporting Non-Expert Annotators with Dynamic Examples from Experts
The success of crowdsourcing based annotation of text corpora depends on...
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05/11/2020
Local Self-Attention over Long Text for Efficient Document Retrieval
Neural networks, particularly Transformer-based architectures, have achi...
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02/04/2020
Interpretable Time-Budget-Constrained Contextualization for Re-Ranking
Search engines operate under a strict time constraint as a fast response...
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01/15/2020
DSR: A Collection for the Evaluation of Graded Disease-Symptom Relations
The effective extraction of ranked disease-symptom relationships is a cr...
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12/10/2019
Neural-IR-Explorer: A Content-Focused Tool to Explore Neural Re-Ranking Results
In this paper we look beyond metrics-based evaluation of Information Ret...
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12/03/2019
TU Wien @ TREC Deep Learning '19 – Simple Contextualization for Re-ranking
The usage of neural network models puts multiple objectives in conflict ...
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07/10/2019
