Jack FitzGerald

According to our database, Jack FitzGerald authored at least 14 papers between 2022 and 2026.

Collaborative distances:

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

2026

Measuring and Eliminating Refusals in Military Large Language Models.

Jack FitzGerald, Dylan Bates, Aristotelis Lazaridis, Aman Sharma, Vincent Lu, Brian King, Yousif Azami, Sean Bailey, Jeremy Cao, Peter Damianov, Kevin de Haan, Joseph Madigan, Jeremy McLaurin, Luke Kerbs, Jonathan Tainer, Dave Anderson, Jonathan Beck, Jamie Cuticello, Colton Malkerson, Tyler Saltsman

CoRR, March, 2026

2025

EdgeRunner 20B: Military Task Parity with GPT-5 while Running on the Edge.

Jack FitzGerald, Aristotelis Lazaridis, Dylan Bates, Aman Sharma, Jonnathan Castillo, Yousif Azami, Sean Bailey, Jeremy Cao, Peter Damianov, Kevin de Haan, Luke Kerbs, Vincent Lu, Joseph Madigan, Jeremy McLaurin, Jonathan Tainer, Dave Anderson, Jonathan Beck, Jamie Cuticello, Colton Malkerson, Tyler Saltsman

CoRR, October, 2025

PHLoRA: data-free Post-hoc Low-Rank Adapter extraction from full-rank checkpoint.

Bhoomit Vasani, Jack FitzGerald, Anjie Fang, Sushmit Vaish

Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics, 2025

Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark.

Goeric Huybrechts, Srikanth Ronanki, Sai Muralidhar Jayanthi, Jack FitzGerald, Srinivasan Veeravanallur

Proceedings of the IEEE/CVF International Conference on Computer Vision, ICCV 2025, 2025

MASSIVE-Agents: A Benchmark for Multilingual Function-Calling in 52 Languages.

Mayank Kulkarni, Vittorio Mazzia, Judith Gaspers, Chris Hench, Jack FitzGerald

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025

Wanda++: Pruning Large Language Models via Regional Gradients.

Yifan Yang, Kai Zhen, Bhavana Ganesh, Aram Galstyan, Goeric Huybrechts, Markus Müller, Jonas M. Kübler, Rupak Vignesh Swaminathan, Athanasios Mouchtaris, Sravan Babu Bodapati, Nathan Susanj, Zheng Zhang, Jack FitzGerald, Abhishek Kumar

Proceedings of the Findings of the Association for Computational Linguistics, 2025

2024

QuAILoRA: Quantization-Aware Initialization for LoRA.

Neal Lawton, Aishwarya Padmakumar, Judith Gaspers, Jack FitzGerald, Anoop Kumar, Greg Ver Steeg, Aram Galstyan

Proceedings of the NeurIPS Efficient Natural Language and Speech Processing Workshop, 2024

MATTER: Memory-Augmented Transformer Using Heterogeneous Knowledge Sources.

Dongkyu Lee, Chandana Satya Prakash, Jack FitzGerald, Jens Lehmann

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

Controlling the Extraction of Memorized Data from Large Language Models via Prompt-Tuning.

Mustafa Özdayi, Charith Peris, Jack FitzGerald, Christophe Dupuy, Jimit Majmudar, Haidar Khan, Rahil Parikh, Rahul Gupta

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2023

MASSIVE: A 1M-Example Multilingual Natural Language Understanding Dataset with 51 Typologically-Diverse Languages.

Jack FitzGerald, Christopher Hench, Charith Peris, Scott Mackie, Kay Rottmann, Ana Sanchez, Aaron Nash, Liam Urbach, Vishesh Kakarala, Richa Singh, Swetha Ranganath, Laurie Crist, Misha Britan, Wouter Leeuwis, Gökhan Tür, Prem Natarajan

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022

The Massively Multilingual Natural Language Understanding 2022 (MMNLU-22) Workshop and Competition.

Christopher Hench, Charith Peris, Jack FitzGerald, Kay Rottmann

CoRR, 2022

AlexaTM 20B: Few-Shot Learning Using a Large-Scale Multilingual Seq2Seq Model.

Saleh Soltan, Shankar Ananthakrishnan, Jack FitzGerald, Rahul Gupta, Wael Hamza, Haidar Khan, Charith Peris, Stephen Rawls, Andy Rosenbaum, Anna Rumshisky, Chandana Satya Prakash, Mukund Sridhar, Fabian Triefenbach, Apurv Verma, Gökhan Tür, Prem Natarajan

CoRR, 2022

Alexa Teacher Model: Pretraining and Distilling Multi-Billion-Parameter Encoders for Natural Language Understanding Systems.

Jack FitzGerald, Shankar Ananthakrishnan, Konstantine Arkoudas, Davide Bernardi, Abhishek Bhagia, Claudio Delli Bovi, Jin Cao, Rakesh Chada, Amit Chauhan, Luoxin Chen, Anurag Dwarakanath, Satyam Dwivedi, Turan Gojayev, Karthik Gopalakrishnan, Thomas Gueudré, Dilek Hakkani-Tur, Wael Hamza, Jonathan J. Hüser, Kevin Martin Jose, Haidar Khan, Beiye Liu, Jianhua Lu, Alessandro Manzotti, Pradeep Natarajan, Karolina Owczarzak, Gokmen Oz, Enrico Palumbo, Charith Peris, Chandana Satya Prakash, Stephen Rawls, Andy Rosenbaum, Anjali Shenoy, Saleh Soltan, Mukund Harakere Sridhar, Liz Tan, Fabian Triefenbach, Pan Wei, Haiyang Yu, Shuai Zheng, Gökhan Tür, Prem Natarajan

CoRR, 2022

Alexa Teacher Model: Pretraining and Distilling Multi-Billion-Parameter Encoders for Natural Language Understanding Systems.

Jack FitzGerald, Shankar Ananthakrishnan, Konstantine Arkoudas, Davide Bernardi, Abhishek Bhagia, Claudio Delli Bovi, Jin Cao, Rakesh Chada, Amit Chauhan, Luoxin Chen, Anurag Dwarakanath, Satyam Dwivedi, Turan Gojayev, Karthik Gopalakrishnan, Thomas Gueudré, Dilek Hakkani-Tur, Wael Hamza, Jonathan J. Hüser, Kevin Martin Jose, Haidar Khan, Beiye Liu, Jianhua Lu, Alessandro Manzotti, Pradeep Natarajan, Karolina Owczarzak, Gokmen Oz, Enrico Palumbo, Charith Peris, Chandana Satya Prakash, Stephen Rawls, Andy Rosenbaum, Anjali Shenoy, Saleh Soltan, Mukund Harakere Sridhar, Lizhen Tan, Fabian Triefenbach, Pan Wei, Haiyang Yu, Shuai Zheng, Gökhan Tür, Prem Natarajan

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022