Sebastian Hofstätter

According to our database, Sebastian Hofstätter authored at least 40 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Replacing Judges with Juries: Evaluating LLM Generations with a Panel of Diverse Models.

Pat Verga, Sebastian Hofstätter, Sophia Althammer, Yixuan Su, Aleksandra Piktus, Arkady Arkhangorodsky, Minjie Xu, Naomi White, Patrick Lewis

CoRR, 2024

2023

Rank-without-GPT: Building GPT-Independent Listwise Rerankers on Open-Source Large Language Models.

Xinyu Zhang, Sebastian Hofstätter, Patrick S. H. Lewis, Raphael Tang, Jimmy Lin

CoRR, 2023

FiD-Light: Efficient and Effective Retrieval-Augmented Text Generation.

Sebastian Hofstätter, Jiecao Chen, Karthik Raman, Hamed Zamani

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Annotating Data for Fine-Tuning a Neural Ranker? Current Active Learning Strategies are not Better than Random Selection.

Sophia Althammer, Guido Zuccon, Sebastian Hofstätter, Suzan Verberne, Allan Hanbury

Proceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region, 2023

Exploring Effect-Size-Based Meta-Analysis for Multi-Dataset Evaluation.

Mete Sertkan, Sophia Althammer, Sebastian Hofstätter, Peter Knees, Julia Neidhardt

Proceedings of the 3rd Workshop Perspectives on the Evaluation of Recommender Systems 2023 co-located with the 17th ACM Conference on Recommender Systems (RecSys 2023), 2023

Search in Archival Facsimile Documents for Digital History.

David Banyasz, Sebastian Hofstätter, Allan Hanbury

Proceedings of the 19th IEEE International Conference on e-Science, 2023

Ranger: A Toolkit for Effect-Size Based Multi-Task Evaluation.

Mete Sertkan, Sophia Althammer, Sebastian Hofstätter

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics: System Demonstrations, 2023

2022

Multi-Task Retrieval-Augmented Text Generation with Relevance Sampling.

Sebastian Hofstätter, Jiecao Chen, Karthik Raman, Hamed Zamani

CoRR, 2022

Are We There Yet? A Decision Framework for Replacing Term Based Retrieval with Dense Retrieval Systems.

Sebastian Hofstätter, Nick Craswell, Bhaskar Mitra, Hamed Zamani, Allan Hanbury

CoRR, 2022

A Time-Optimized Content Creation Workflow for Remote Teaching.

Sebastian Hofstätter, Sophia Althammer, Mete Sertkan, Allan Hanbury

Proceedings of the SIGCSE 2022: The 53rd ACM Technical Symposium on Computer Science Education, 2022

Diversifying Sentiments in News Recommendation.

Mete Sertkan, Sophia Althammer, Sebastian Hofstätter, Julia Neidhardt

Proceedings of the Perspectives on the Evaluation of Recommender Systems Workshop 2022 co-located with the 16th ACM Conference on Recommender Systems (RecSys 2022), 2022

Establishing Strong Baselines For TripClick Health Retrieval.

Sebastian Hofstätter, Sophia Althammer, Mete Sertkan, Allan Hanbury

Proceedings of the Advances in Information Retrieval, 2022

PARM: A Paragraph Aggregation Retrieval Model for Dense Document-to-Document Retrieval.

Sophia Althammer, Sebastian Hofstätter, Mete Sertkan, Suzan Verberne, Allan Hanbury

Proceedings of the Advances in Information Retrieval, 2022

Introducing Neural Bag of Whole-Words with ColBERTer: Contextualized Late Interactions using Enhanced Reduction.

Sebastian Hofstätter, Omar Khattab, Sophia Althammer, Mete Sertkan, Allan Hanbury

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

TripJudge: A Relevance Judgement Test Collection for TripClick Health Retrieval.

Sophia Althammer, Sebastian Hofstätter, Suzan Verberne, Allan Hanbury

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021

Linguistically Informed Masking for Representation Learning in the Patent Domain.

Sophia Althammer, Mark Buckley, Sebastian Hofstätter, Allan Hanbury

CoRR, 2021

TU Wien at TREC DL and Podcast 2021: Simple Compression for Dense Retrieval.

Sebastian Hofstätter, Mete Sertkan, Allan Hanbury

Proceedings of the Thirtieth Text REtrieval Conference, 2021

Improving Transformer-Kernel Ranking Model Using Conformer and Query Term Independence.

Bhaskar Mitra, Sebastian Hofstätter, Hamed Zamani, Nick Craswell

Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

Intra-Document Cascading: Learning to Select Passages for Neural Document Ranking.

Sebastian Hofstätter, Bhaskar Mitra, Hamed Zamani, Nick Craswell, Allan Hanbury

Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

Efficiently Teaching an Effective Dense Retriever with Balanced Topic Aware Sampling.

Sebastian Hofstätter, Sheng-Chieh Lin, Jheng-Hong Yang, Jimmy Lin, Allan Hanbury

Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

Mitigating the Position Bias of Transformer Models in Passage Re-ranking.

Sebastian Hofstätter, Aldo Lipani, Sophia Althammer, Markus Zlabinger, Allan Hanbury

Proceedings of the Advances in Information Retrieval, 2021

Cross-Domain Retrieval in the Legal and Patent Domains: A Reproducibility Study.

Sophia Althammer, Sebastian Hofstätter, Allan Hanbury

Proceedings of the Advances in Information Retrieval, 2021

2020

Cross-domain Retrieval in the Legal and Patent Domains: a Reproducability Study.

Sophia Althammer, Sebastian Hofstätter, Allan Hanbury

CoRR, 2020

Improving Efficient Neural Ranking Models with Cross-Architecture Knowledge Distillation.

Sebastian Hofstätter, Sophia Althammer, Michael Schröder, Mete Sertkan, Allan Hanbury

CoRR, 2020

Conformer-Kernel with Query Term Independence for Document Retrieval.

Bhaskar Mitra, Sebastian Hofstätter, Hamed Zamani, Nick Craswell

CoRR, 2020

Conformer-Kernel with Query Term Independence at TREC 2020 Deep Learning Track.

Bhaskar Mitra, Sebastian Hofstätter, Hamed Zamani, Nick Craswell

Proceedings of the Twenty-Ninth Text REtrieval Conference, 2020

Evaluating Transformer-Kernel Models at TREC Deep Learning 2020.

Sebastian Hofstätter, Allan Hanbury

Proceedings of the Twenty-Ninth Text REtrieval Conference, 2020

DEXA: Supporting Non-Expert Annotators with Dynamic Examples from Experts.

Markus Zlabinger, Marta Sabou, Sebastian Hofstätter, Mete Sertkan, Allan Hanbury

Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

Local Self-Attention over Long Text for Efficient Document Retrieval.

Sebastian Hofstätter, Hamed Zamani, Bhaskar Mitra, Nick Craswell, Allan Hanbury

Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

End-to-End Contextualized Document Indexing and Retrieval with Neural Networks.

Sebastian Hofstätter

Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

Effective Crowd-Annotation of Participants, Interventions, and Outcomes in the Text of Clinical Trial Reports.

Markus Zlabinger, Marta Sabou, Sebastian Hofstätter, Allan Hanbury

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

DSR: A Collection for the Evaluation of Graded Disease-Symptom Relations.

Markus Zlabinger, Sebastian Hofstätter, Navid Rekabsaz, Allan Hanbury

Proceedings of the Advances in Information Retrieval, 2020

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

Sebastian Hofstätter, Markus Zlabinger, Allan Hanbury

Proceedings of the Advances in Information Retrieval, 2020

Interpretable & Time-Budget-Constrained Contextualization for Re-Ranking.

Sebastian Hofstätter, Markus Zlabinger, Allan Hanbury

Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

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

Sebastian Hofstätter, Markus Zlabinger, Mete Sertkan, Michael Schröder, Allan Hanbury

Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

Learning to Re-Rank with Contextualized Stopwords.

Sebastian Hofstätter, Aldo Lipani, Markus Zlabinger, Allan Hanbury

Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

2019

TU Wien @ TREC Deep Learning '19 - Simple Contextualization for Re-ranking.

Sebastian Hofstätter, Markus Zlabinger, Allan Hanbury

Proceedings of the Twenty-Eighth Text REtrieval Conference, 2019

On the Effect of Low-Frequency Terms on Neural-IR Models.

Sebastian Hofstätter, Navid Rekabsaz, Carsten Eickhoff, Allan Hanbury

Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2019

Let's measure run time! Extending the IR replicability infrastructure to include performance aspects.

Sebastian Hofstätter, Allan Hanbury

Proceedings of the Open-Source IR Replicability Challenge co-located with 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2019

Enriching Word Embeddings for Patent Retrieval with Global Context.

Sebastian Hofstätter, Navid Rekabsaz, Mihai Lupu, Carsten Eickhoff, Allan Hanbury

Proceedings of the Advances in Information Retrieval, 2019