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Nicholas FitzGerald
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2020 – today
- 2024
- [j3]Javier Cabrera-Arteaga
, Nicholas FitzGerald, Martin Monperrus
, Benoit Baudry
:
Wasm-Mutate: Fast and effective binary diversification for WebAssembly. Comput. Secur. 139: 103731 (2024) - 2023
- [c15]Michiel de Jong, Yury Zemlyanskiy, Joshua Ainslie, Nicholas FitzGerald, Sumit Sanghai, Fei Sha, William W. Cohen:
FiDO: Fusion-in-Decoder optimized for stronger performance and faster inference. ACL (Findings) 2023: 11534-11547 - [c14]Michiel de Jong, Yury Zemlyanskiy, Nicholas FitzGerald, Joshua Ainslie, Sumit Sanghai, Fei Sha, William W. Cohen:
Pre-computed memory or on-the-fly encoding? A hybrid approach to retrieval augmentation makes the most of your compute. ICML 2023: 7329-7342 - [i12]Michiel de Jong, Yury Zemlyanskiy, Nicholas FitzGerald, Joshua Ainslie, Sumit Sanghai, Fei Sha, William W. Cohen:
Pre-computed memory or on-the-fly encoding? A hybrid approach to retrieval augmentation makes the most of your compute. CoRR abs/2301.10448 (2023) - [i11]Michiel de Jong, Yury Zemlyanskiy, Nicholas FitzGerald, Sumit Sanghai, William W. Cohen, Joshua Ainslie:
GLIMMER: generalized late-interaction memory reranker. CoRR abs/2306.10231 (2023) - [i10]Javier Cabrera-Arteaga, Nicholas FitzGerald, Martin Monperrus, Benoit Baudry:
WASM-MUTATE: Fast and Effective Binary Diversification for WebAssembly. CoRR abs/2309.07638 (2023) - 2022
- [c13]Michiel de Jong, Yury Zemlyanskiy, Nicholas FitzGerald, Fei Sha, William W. Cohen:
Mention Memory: incorporating textual knowledge into Transformers through entity mention attention. ICLR 2022 - [i9]Michiel de Jong, Yury Zemlyanskiy, Joshua Ainslie, Nicholas FitzGerald, Sumit Sanghai, Fei Sha, William W. Cohen:
FiDO: Fusion-in-Decoder optimized for stronger performance and faster inference. CoRR abs/2212.08153 (2022) - 2021
- [c12]Nicholas FitzGerald, Daniel M. Bikel, Jan A. Botha, Daniel Gillick, Tom Kwiatkowski, Andrew McCallum:
MOLEMAN: Mention-Only Linking of Entities with a Mention Annotation Network. ACL/IJCNLP (2) 2021: 278-285 - [i8]Nicholas FitzGerald, Jan A. Botha, Daniel Gillick, Daniel M. Bikel, Tom Kwiatkowski, Andrew McCallum:
MOLEMAN: Mention-Only Linking of Entities with a Mention Annotation Network. CoRR abs/2106.07352 (2021) - [i7]Michiel de Jong, Yury Zemlyanskiy, Nicholas FitzGerald, Fei Sha, William W. Cohen:
Mention Memory: incorporating textual knowledge into Transformers through entity mention attention. CoRR abs/2110.06176 (2021) - 2020
- [c11]Thibault Févry, Nicholas FitzGerald, Livio Baldini Soares, Tom Kwiatkowski:
Empirical Evaluation of Pretraining Strategies for Supervised Entity Linking. AKBC 2020 - [c10]Thibault Févry, Livio Baldini Soares, Nicholas FitzGerald, Eunsol Choi, Tom Kwiatkowski:
Entities as Experts: Sparse Memory Access with Entity Supervision. EMNLP (1) 2020: 4937-4951 - [i6]Jeffrey Ling, Nicholas FitzGerald, Zifei Shan, Livio Baldini Soares, Thibault Févry, David Weiss, Tom Kwiatkowski:
Learning Cross-Context Entity Representations from Text. CoRR abs/2001.03765 (2020) - [i5]Thibault Févry, Livio Baldini Soares, Nicholas FitzGerald, Eunsol Choi, Tom Kwiatkowski:
Entities as Experts: Sparse Memory Access with Entity Supervision. CoRR abs/2004.07202 (2020) - [i4]Thibault Févry, Nicholas FitzGerald, Livio Baldini Soares, Tom Kwiatkowski:
Empirical Evaluation of Pretraining Strategies for Supervised Entity Linking. CoRR abs/2005.14253 (2020)
2010 – 2019
- 2019
- [c9]Livio Baldini Soares, Nicholas FitzGerald, Jeffrey Ling, Tom Kwiatkowski:
Matching the Blanks: Distributional Similarity for Relation Learning. ACL (1) 2019: 2895-2905 - [i3]Livio Baldini Soares, Nicholas FitzGerald, Jeffrey Ling, Tom Kwiatkowski:
Matching the Blanks: Distributional Similarity for Relation Learning. CoRR abs/1906.03158 (2019) - 2018
- [b1]Nicholas FitzGerald:
Neural Models for Large-Scale Semantic Role Labelling. University of Washington, USA, 2018 - [c8]Omer Levy, Kenton Lee, Nicholas FitzGerald, Luke Zettlemoyer:
Long Short-Term Memory as a Dynamically Computed Element-wise Weighted Sum. ACL (2) 2018: 732-739 - [c7]Nicholas FitzGerald, Julian Michael, Luheng He, Luke Zettlemoyer:
Large-Scale QA-SRL Parsing. ACL (1) 2018: 2051-2060 - [i2]Omer Levy, Kenton Lee, Nicholas FitzGerald, Luke Zettlemoyer:
Long Short-Term Memory as a Dynamically Computed Element-wise Weighted Sum. CoRR abs/1805.03716 (2018) - [i1]Nicholas FitzGerald, Julian Michael, Luheng He, Luke Zettlemoyer:
Large-Scale QA-SRL Parsing. CoRR abs/1805.05377 (2018) - 2015
- [j2]Kent Rosser, Karl Pavey, Nicholas FitzGerald, Anselm Fatiaki, Daniel Neumann, David Carr, Brian Hanlon, Javaan S. Chahl
:
Autonomous Chemical Vapour Detection by Micro UAV. Remote. Sens. 7(12): 16865-16882 (2015) - [c6]Nicholas FitzGerald, Oscar Täckström, Kuzman Ganchev, Dipanjan Das:
Semantic Role Labeling with Neural Network Factors. EMNLP 2015: 960-970 - 2013
- [c5]Yoav Artzi, Nicholas FitzGerald, Luke Zettlemoyer:
Semantic Parsing with Combinatory Categorial Grammars. ACL (Tutorial Abstracts) 2013: 2 - [c4]Nicholas FitzGerald, Yoav Artzi, Luke Zettlemoyer:
Learning Distributions over Logical Forms for Referring Expression Generation. EMNLP 2013: 1914-1925 - 2012
- [j1]Jan Wildenhain
, Nicholas FitzGerald, Mike Tyers:
MolClass: a web portal to interrogate diverse small molecule screen datasets with different computational models. Bioinform. 28(16): 2200-2201 (2012) - [c3]Cynthia Matuszek, Nicholas FitzGerald, Luke Zettlemoyer, Liefeng Bo, Dieter Fox:
A Joint Model of Language and Perception for Grounded Attribute Learning. ICML 2012 - 2011
- [c2]Cristina Conati, Giuseppe Carenini, Mona Harati, Dereck Toker, Nicholas FitzGerald, Anna Flagg:
User-Adaptive Visualizations: Can Gaze Data Tell Us When a User Needs Them? Scalable Integration of Analytics and Visualization 2011 - [c1]Nicholas FitzGerald, Giuseppe Carenini, Gabriel Murray, Shafiq R. Joty:
Exploiting Conversational Features to Detect High-Quality Blog Comments. Canadian AI 2011: 122-127
Coauthor Index
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