Sean MacAvaney

research

∙ 08/01/2023

On the Effects of Regional Spelling Conventions in Retrieval Models

One advantage of neural ranking models is that they are meant to general...

0 Andreas Chari, et al. ∙

research

∙ 08/01/2023

Generative Query Reformulation for Effective Adhoc Search

Performing automatic reformulations of a user's query is a popular parad...

0 Xiao Wang, et al. ∙

research

∙ 07/31/2023

Lexically-Accelerated Dense Retrieval

Retrieval approaches that score documents based on learned dense vectors...

0 Hrishikesh Kulkarni, et al. ∙

research

∙ 06/29/2023

Re-Rank - Expand - Repeat: Adaptive Query Expansion for Document Retrieval Using Words and Entities

Sparse and dense pseudo-relevance feedback (PRF) approaches perform poor...

0 Iain Mackie, et al. ∙

research

∙ 05/30/2023

The Information Retrieval Experiment Platform

We integrate ir_datasets, ir_measures, and PyTerrier with TIRA in the In...

0 Maik Fröbe, et al. ∙

research

∙ 05/29/2023

Adapting Learned Sparse Retrieval for Long Documents

Learned sparse retrieval (LSR) is a family of neural retrieval methods t...

0 Thong Nguyen, et al. ∙

research

∙ 04/24/2023

Overview of the TREC 2022 NeuCLIR Track

This is the first year of the TREC Neural CLIR (NeuCLIR) track, which ai...

0 Dawn Lawrie, et al. ∙

research

∙ 03/23/2023

A Unified Framework for Learned Sparse Retrieval

Learned sparse retrieval (LSR) is a family of first-stage retrieval meth...

0 Thong Nguyen, et al. ∙

research

∙ 02/22/2023

One-Shot Labeling for Automatic Relevance Estimation

Dealing with unjudged documents ("holes") in relevance assessments is a ...

0 Sean MacAvaney, et al. ∙

research

∙ 01/09/2023

Doc2Query–: When Less is More

Doc2Query – the process of expanding the content of a document before in...

0 Mitko Gospodinov, et al. ∙

research

∙ 08/18/2022

Adaptive Re-Ranking with a Corpus Graph

Search systems often employ a re-ranking pipeline, wherein documents (or...

0 Sean MacAvaney, et al. ∙

research

∙ 05/09/2022

CODEC: Complex Document and Entity Collection

CODEC is a document and entity ranking benchmark that focuses on complex...

0 Iain Mackie, et al. ∙

research

∙ 04/27/2022

On Survivorship Bias in MS MARCO

Survivorship bias is the tendency to concentrate on the positive outcome...

0 Prashansa Gupta, et al. ∙

research

∙ 01/21/2022

Reproducing Personalised Session Search over the AOL Query Log

Despite its troubled past, the AOL Query Log continues to be an importan...

0 Sean MacAvaney, et al. ∙

research

∙ 11/26/2021

Streamlining Evaluation with ir-measures

We present ir-measures, a new tool that makes it convenient to calculate...

0 Sean MacAvaney, et al. ∙

research

∙ 08/31/2021

Max-Utility Based Arm Selection Strategy For Sequential Query Recommendations

We consider the query recommendation problem in closed loop interactive ...

0 Shameem A Puthiya Parambath, et al. ∙

research

∙ 08/09/2021

IntenT5: Search Result Diversification using Causal Language Models

Search result diversification is a beneficial approach to overcome under...

0 Sean MacAvaney, et al. ∙

research

∙ 05/03/2021

Goldilocks: Just-Right Tuning of BERT for Technology-Assisted Review

Technology-assisted review (TAR) refers to iterative active learning wor...

0 Eugene Yang, et al. ∙

research

∙ 03/03/2021

Simplified Data Wrangling with ir_datasets

Managing the data for Information Retrieval (IR) experiments can be chal...

9 Sean MacAvaney, et al. ∙

research

∙ 03/01/2021

ToxCCIn: Toxic Content Classification with Interpretability

Despite the recent successes of transformer-based models in terms of eff...

0 Tong Xiang, et al. ∙

research

∙ 11/02/2020

ABNIRML: Analyzing the Behavior of Neural IR Models

Numerous studies have demonstrated the effectiveness of pretrained conte...

2 Sean MacAvaney, et al. ∙

research

∙ 10/12/2020

SLEDGE-Z: A Zero-Shot Baseline for COVID-19 Literature Search

With worldwide concerns surrounding the Severe Acute Respiratory Syndrom...

10 Sean MacAvaney, et al. ∙

research

∙ 08/20/2020

PARADE: Passage Representation Aggregation for Document Reranking

We present PARADE, an end-to-end Transformer-based model that considers ...

0 Canjia Li, et al. ∙

research

∙ 07/28/2020

GUIR at SemEval-2020 Task 12: Domain-Tuned Contextualized Models for Offensive Language Detection

Offensive language detection is an important and challenging task in nat...

0 Sajad Sotudeh, et al. ∙

research

∙ 05/18/2020

Interaction Matching for Long-Tail Multi-Label Classification

We present an elegant and effective approach for addressing limitations ...

0 Sean MacAvaney, et al. ∙

research

∙ 05/05/2020

SLEDGE: A Simple Yet Effective Baseline for Coronavirus Scientific Knowledge Search

With worldwide concerns surrounding the Severe Acute Respiratory Syndrom...

0 Sean MacAvaney, et al. ∙

research

∙ 04/29/2020

Training Curricula for Open Domain Answer Re-Ranking

In precision-oriented tasks like answer ranking, it is more important to...

0 Sean MacAvaney, et al. ∙

research

∙ 04/29/2020

Efficient Document Re-Ranking for Transformers by Precomputing Term Representations

Deep pretrained transformer networks are effective at various ranking ta...

0 Sean MacAvaney, et al. ∙

research

∙ 04/29/2020

Expansion via Prediction of Importance with Contextualization

The identification of relevance with little textual context is a primary...

0 Sean MacAvaney, et al. ∙

research

∙ 01/18/2020

Ranking Significant Discrepancies in Clinical Reports

Medical errors are a major public health concern and a leading cause of ...

0 Sean MacAvaney, et al. ∙

research

∙ 12/30/2019

Teaching a New Dog Old Tricks: Resurrecting Multilingual Retrieval Using Zero-shot Learning

While billions of non-English speaking users rely on search engines ever...

0 Sean MacAvaney, et al. ∙

research

∙ 05/14/2019

Ontology-Aware Clinical Abstractive Summarization

Automatically generating accurate summaries from clinical reports could ...

0 Sean MacAvaney, et al. ∙

research

∙ 04/15/2019

CEDR: Contextualized Embeddings for Document Ranking

Although considerable attention has been given to neural ranking archite...

0 Sean MacAvaney, et al. ∙

research

∙ 04/15/2019

Contextualized Word Representations for Document Re-Ranking

Although considerable attention has been given to neural ranking archite...

0 Sean MacAvaney, et al. ∙

research

∙ 11/21/2018

Overcoming low-utility facets for complex answer retrieval

Many questions cannot be answered simply; their answers must include num...

0 Sean MacAvaney, et al. ∙

research

∙ 06/20/2018

RSDD-Time: Temporal Annotation of Self-Reported Mental Health Diagnoses

Self-reported diagnosis statements have been widely employed in studying...

1 Sean MacAvaney, et al. ∙

research

∙ 06/13/2018

SMHD: A Large-Scale Resource for Exploring Online Language Usage for Multiple Mental Health Conditions

Mental health is a significant and growing public health concern. As lan...

1 Arman Cohan, et al. ∙

research

∙ 05/02/2018

Characterizing Question Facets for Complex Answer Retrieval

Complex answer retrieval (CAR) is the process of retrieving answers to q...

0 Sean MacAvaney, et al. ∙

research

∙ 04/16/2018

A Deeper Look into Dependency-Based Word Embeddings

We investigate the effect of various dependency-based word embeddings on...

0 Sean MacAvaney, et al. ∙

research

∙ 04/15/2018

GU IRLAB at SemEval-2018 Task 7: Tree-LSTMs for Scientific Relation Classification

SemEval 2018 Task 7 focuses on relation ex- traction and classification ...

0 Sean MacAvaney, et al. ∙

research

∙ 07/01/2017

An Approach for Weakly-Supervised Deep Information Retrieval

Recent developments in neural information retrieval models have been pro...

0 Sean MacAvaney, et al. ∙

Sean MacAvaney

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