Ian Soboroff
Artificial Intelligence · 2002–2021
A researcher in the Science corpus: 14 papers; trusts 11 researchers and is trusted by 28 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 35 citations into it; #29,915 of 35,345 by trust here, #16,166 by citations
- Information Retrieval & Search — 35 citations into it; #491 of 1,022 by trust here, #663 by citations
- Evaluation & Benchmarks — 22 citations into it; #753 of 3,147 by trust here, #1,895 by citations
- Information Systems — 22 citations into it; #7,104 of 8,771 by trust here, #2,912 by citations
- Natural Language Processing — 7 citations into it; #1,765 of 5,688 by trust here, #3,897 by citations
Whom Ian Soboroff trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Stephen E. Robertson
- Ellen M. Voorhees
- Chris Buckley
- Justin Zobel
- Iadh Ounis
- Emine Yilmaz
- Bhaskar Mitra
- Craig Macdonald
- Jimmy J. Lin
- J. Aslam
Who trusts Ian Soboroff overall
- Jimmy J. Lin
- Aliaksei Severyn
- Rodrigo Nogueira
- Walid Magdy
- Miles Efron
- William R. Hersh
- Nick Craswell
- Cheng Li
- Andrew Yates
- Alessandro Moschitti
Papers from Ian Soboroff's perspective
Ordered by how strongly the researchers Ian Soboroff trusts endorse each paper. Same corpus, a different order for every researcher.
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Cumulated gain-based evaluation of IR techniques
- Retrieval evaluation with incomplete information
- Automatic differentiation in PyTorch
- XLNet: Generalized Autoregressive Pretraining for Language Understanding (Neural Information Processing Systems)
- Bag of Tricks for Efficient Text Classification
- MS MARCO: A Human Generated MAchine Reading COmprehension Dataset
- How reliable are the results of large-scale information retrieval experiments?
- An Introduction to Neural Information Retrieval
- Learning to Match using Local and Distributed Representations of Text for Web Search
Their papers
- TREC-COVID: rationale and structure of an information retrieval shared task for COVID-19 (2020) — 130 citations
- TREC-COVID (2020) — 94 citations
- Relevance assessment: are judges exchangeable and does it matter (2008) — 216 citations
- TREC Deep Learning Track: Reusable Test Collections in the Large Data Regime (2021) — 73 citations
- Overview of TREC 2021 (2021) — 30 citations
- TREC 2018 News Track Overview (2018) — 63 citations
- Overview of the TREC-2012 Microblog Track (2014) — 141 citations
- On building a reusable Twitter corpus (2012) — 92 citations
- Overview of the TREC 2011 Microblog Track (2011) — 246 citations
- Overview of the TREC 2009 Web Track (2009) — 437 citations
- The ICWSM 2009 Spinn3r Dataset (2009) — 171 citations
- Bias and the limits of pooling for large collections (2007) — 147 citations
- Overview of the TREC 2005 Enterprise Track (2005) — 397 citations
- The TREC 2002 Filtering Track Report (2002) — 255 citations