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2020 – today
- 2024
[c20]Zachary Ankner, Naomi Saphra, Davis W. Blalock, Jonathan Frankle, Matthew L. Leavitt:
Dynamic Masking Rate Schedules for MLM Pretraining. EACL (2) 2024: 477-487- [c19]Victoria R. Li, Yida Chen, Naomi Saphra:
ChatGPT Doesn't Trust Chargers Fans: Guardrail Sensitivity in Context. EMNLP 2024: 6327-6345 - [c18]Adir Rahamim, Naomi Saphra, Sara Kangaslahti, Yonatan Belinkov:
Fast Forwarding Low-Rank Training. EMNLP 2024: 9553-9562 - [c17]Ian Berlot-Attwell, Kumar Krishna Agrawal, Annabelle Michael Carrell, Yash Sharma, Naomi Saphra:
Attribute Diversity Determines the Systematicity Gap in VQA. EMNLP 2024: 9576-9611 - [c16]Angelica Chen, Ravid Shwartz-Ziv, Kyunghyun Cho, Matthew L. Leavitt, Naomi Saphra
:
Sudden Drops in the Loss: Syntax Acquisition, Phase Transitions, and Simplicity Bias in MLMs. ICLR 2024 - [c15]Tom Sherborne, Naomi Saphra, Pradeep Dasigi, Hao Peng:
TRAM: Bridging Trust Regions and Sharpness Aware Minimization. ICLR 2024 - [c14]Naomi Saphra, Eve Fleisig, Kyunghyun Cho, Adam Lopez:
First Tragedy, then Parse: History Repeats Itself in the New Era of Large Language Models. NAACL-HLT 2024: 2310-2326 - [i28]Divyansh Singhvi, Andrej Erkelens, Raghav Jain, Diganta Misra, Naomi Saphra:
Knowing Your Nonlinearities: Shapley Interactions Reveal the Underlying Structure of Data. CoRR abs/2403.13106 (2024) - [i27]Edwin Zhang, Vincent Zhu, Naomi Saphra, Anat Kleiman, Benjamin L. Edelman, Milind Tambe, Sham M. Kakade, Eran Malach:
Transcendence: Generative Models Can Outperform The Experts That Train Them. CoRR abs/2406.11741 (2024) - [i26]USVSN Sai Prashanth, Alvin Deng, Kyle O'Brien, Jyothir S. V, Mohammad Aflah Khan, Jaydeep Borkar, Christopher A. Choquette-Choo, Jacob Ray Fuehne, Stella Biderman, Tracy Ke, Katherine Lee, Naomi Saphra:
Recite, Reconstruct, Recollect: Memorization in LMs as a Multifaceted Phenomenon. CoRR abs/2406.17746 (2024) - [i25]Victoria R. Li, Yida Chen, Naomi Saphra:
ChatGPT Doesn't Trust Chargers Fans: Guardrail Sensitivity in Context. CoRR abs/2407.06866 (2024) - [i24]Michael Saxon, Ari Holtzman, Peter West, William Yang Wang, Naomi Saphra:
Benchmarks as Microscopes: A Call for Model Metrology. CoRR abs/2407.16711 (2024) - [i23]Adir Rahamim, Naomi Saphra, Sara Kangaslahti, Yonatan Belinkov:
Fast Forwarding Low-Rank Training. CoRR abs/2409.04206 (2024) - 2023
- [j2]Dieuwke Hupkes, Mario Giulianelli, Verna Dankers, Mikel Artetxe, Yanai Elazar, Tiago Pimentel, Christos E. Christodoulopoulos, Karim Lasri, Naomi Saphra, Arabella Sinclair, Dennis Ulmer, Florian Schottmann, Khuyagbaatar Batsuren, Kaiser Sun, Koustuv Sinha, Leila Khalatbari, Maria Ryskina, Rita Frieske, Ryan Cotterell, Zhijing Jin:
A taxonomy and review of generalization research in NLP. Nat. Mac. Intell. 5(10): 1161-1174 (2023) - [j1]Michael Y. Hu, Angelica Chen, Naomi Saphra, Kyunghyun Cho:
Latent State Models of Training Dynamics. Trans. Mach. Learn. Res. 2023 (2023) - [c13]Jeevesh Juneja, Rachit Bansal, Kyunghyun Cho, João Sedoc, Naomi Saphra:
Linear Connectivity Reveals Generalization Strategies. ICLR 2023 - [e3]Burcu Can, Maximilian Mozes, Samuel Cahyawijaya, Naomi Saphra, Nora Kassner, Shauli Ravfogel, Abhilasha Ravichander, Chen Zhao, Isabelle Augenstein, Anna Rogers, Kyunghyun Cho, Edward Grefenstette, Lena Voita:
Proceedings of the 8th Workshop on Representation Learning for NLP, RepL4NLP@ACL 2023, Toronto, Canada, July 13, 2023. Association for Computational Linguistics 2023, ISBN 978-1-959429-77-7 [contents] - [i22]Zachary Ankner, Naomi Saphra, Davis W. Blalock, Jonathan Frankle, Matthew L. Leavitt:
Dynamic Masking Rate Schedules for MLM Pretraining. CoRR abs/2305.15096 (2023) - [i21]Michael Y. Hu, Angelica Chen, Naomi Saphra, Kyunghyun Cho:
Latent State Models of Training Dynamics. CoRR abs/2308.09543 (2023) - [i20]Angelica Chen, Ravid Shwartz-Ziv, Kyunghyun Cho, Matthew L. Leavitt, Naomi Saphra:
Sudden Drops in the Loss: Syntax Acquisition, Phase Transitions, and Simplicity Bias in MLMs. CoRR abs/2309.07311 (2023) - [i19]Tom Sherborne, Naomi Saphra, Pradeep Dasigi, Hao Peng:
TRAM: Bridging Trust Regions and Sharpness Aware Minimization. CoRR abs/2310.03646 (2023) - [i18]Naomi Saphra, Eve Fleisig, Kyunghyun Cho, Adam Lopez:
First Tragedy, then Parse: History Repeats Itself in the New Era of Large Language Models. CoRR abs/2311.05020 (2023) - [i17]Ian Berlot-Attwell, A. Michael Carrell, Kumar Krishna Agrawal, Yash Sharma, Naomi Saphra:
Attribute Diversity Determines the Systematicity Gap in VQA. CoRR abs/2311.08695 (2023) - [i16]Yash Gondhalekar, Sultan Hassan, Naomi Saphra, Sambatra Andrianomena:
Towards out-of-distribution generalization in large-scale astronomical surveys: robust networks learn similar representations. CoRR abs/2311.18007 (2023) - 2022
- [c12]Josef Valvoda, Naomi Saphra, Jonathan Rawski, Adina Williams, Ryan Cotterell:
Benchmarking Compositionality with Formal Languages. COLING 2022: 6007-6018 - [c11]Thibault Sellam, Steve Yadlowsky, Ian Tenney, Jason Wei, Naomi Saphra, Alexander D'Amour, Tal Linzen, Jasmijn Bastings, Iulia Raluca Turc, Jacob Eisenstein, Dipanjan Das, Ellie Pavlick:
The MultiBERTs: BERT Reproductions for Robustness Analysis. ICLR 2022 - [e2]Jasmijn Bastings, Yonatan Belinkov, Yanai Elazar, Dieuwke Hupkes, Naomi Saphra, Sarah Wiegreffe:
Proceedings of the Fifth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, BlackboxNLP@EMNLP 2022, Abu Dhabi, United Arab Emirates (Hybrid), December 8, 2022. Association for Computational Linguistics 2022, ISBN 978-1-959429-05-0 [contents] - [i15]Jeevesh Juneja, Rachit Bansal, Kyunghyun Cho, João Sedoc, Naomi Saphra:
Linear Connectivity Reveals Generalization Strategies. CoRR abs/2205.12411 (2022) - [i14]Josef Valvoda, Naomi Saphra, Jonathan Rawski, Ryan Cotterell, Adina Williams:
Learning Transductions to Test Systematic Compositionality. CoRR abs/2208.08195 (2022) - [i13]Dieuwke Hupkes, Mario Giulianelli, Verna Dankers, Mikel Artetxe, Yanai Elazar, Tiago Pimentel, Christos Christodoulopoulos, Karim Lasri, Naomi Saphra, Arabella Sinclair, Dennis Ulmer, Florian Schottmann, Khuyagbaatar Batsuren, Kaiser Sun, Koustuv Sinha, Leila Khalatbari, Maria Ryskina, Rita Frieske, Ryan Cotterell, Zhijing Jin:
State-of-the-art generalisation research in NLP: a taxonomy and review. CoRR abs/2210.03050 (2022) - [i12]Bingchen Zhao, Yuling Gu, Jessica Zosa Forde, Naomi Saphra:
One Venue, Two Conferences: The Separation of Chinese and American Citation Networks. CoRR abs/2211.12424 (2022) - 2021
- [c10]Jennifer C. White, Tiago Pimentel, Naomi Saphra, Ryan Cotterell:
A Non-Linear Structural Probe. NAACL-HLT 2021: 132-138 - [e1]Anna Rogers, Iacer Calixto, Ivan Vulic, Naomi Saphra, Nora Kassner, Oana-Maria Camburu, Trapit Bansal, Vered Shwartz:
Proceedings of the 6th Workshop on Representation Learning for NLP, RepL4NLP@ACL-IJCNLP 2021, Online, August 6, 2021. Association for Computational Linguistics 2021, ISBN 978-1-954085-72-5 [contents] - [i11]Jennifer C. White, Tiago Pimentel, Naomi Saphra, Ryan Cotterell:
A Non-Linear Structural Probe. CoRR abs/2105.10185 (2021) - [i10]Thibault Sellam, Steve Yadlowsky, Jason Wei, Naomi Saphra, Alexander D'Amour, Tal Linzen, Jasmijn Bastings, Iulia Turc, Jacob Eisenstein, Dipanjan Das, Ian Tenney, Ellie Pavlick:
The MultiBERTs: BERT Reproductions for Robustness Analysis. CoRR abs/2106.16163 (2021) - 2020
- [c9]Mohammad Tahaei, Kami Vaniea, Naomi Saphra:
Understanding Privacy-Related Questions on Stack Overflow. CHI 2020: 1-14 - [c8]Naomi Saphra, Adam Lopez:
LSTMS Compose - and Learn - Bottom-Up. EMNLP (Findings) 2020: 2797-2809 - [c7]Tiago Pimentel, Naomi Saphra, Adina Williams, Ryan Cotterell:
Pareto Probing: Trading Off Accuracy for Complexity. EMNLP (1) 2020: 3138-3153 - [i9]Naomi Saphra, Adam Lopez:
Word Interdependence Exposes How LSTMs Compose Representations. CoRR abs/2004.13195 (2020) - [i8]Tiago Pimentel, Naomi Saphra, Adina Williams, Ryan Cotterell:
Pareto Probing: Trading Off Accuracy for Complexity. CoRR abs/2010.02180 (2020) - [i7]Naomi Saphra, Adam Lopez:
LSTMs Compose (and Learn) Bottom-Up. CoRR abs/2010.04650 (2020)
2010 – 2019
- 2019
- [c6]Naomi Saphra, Adam Lopez:
Understanding Learning Dynamics Of Language Models with SVCCA. NAACL-HLT (1) 2019: 3257-3267 - [i6]Naomi Saphra, Adam Lopez:
Sparsity Emerges Naturally in Neural Language Models. CoRR abs/1908.01817 (2019) - [i5]Yekun Chai, Naomi Saphra, Adam Lopez:
How to Evaluate Word Representations of Informal Domain? CoRR abs/1911.04669 (2019) - 2018
- [c5]Naomi Saphra, Adam Lopez:
Language Models Learn POS First. BlackboxNLP@EMNLP 2018: 328-330 - [i4]Naomi Saphra, Adam Lopez:
Understanding Learning Dynamics Of Language Models with SVCCA. CoRR abs/1811.00225 (2018) - 2017
- [i3]Graham Neubig, Chris Dyer, Yoav Goldberg, Austin Matthews, Waleed Ammar, Antonios Anastasopoulos, Miguel Ballesteros, David Chiang, Daniel Clothiaux, Trevor Cohn, Kevin Duh, Manaal Faruqui, Cynthia Gan, Dan Garrette, Yangfeng Ji, Lingpeng Kong, Adhiguna Kuncoro, Gaurav Kumar, Chaitanya Malaviya, Paul Michel, Yusuke Oda, Matthew Richardson, Naomi Saphra, Swabha Swayamdipta, Pengcheng Yin:
DyNet: The Dynamic Neural Network Toolkit. CoRR abs/1701.03980 (2017) - 2016
- [c4]Naomi Saphra:
Evaluating Informal-Domain Word Representations With UrbanDictionary. RepEval@ACL 2016: 94-98 - [i2]Naomi Saphra, Adam Lopez:
Evaluating Informal-Domain Word Representations With UrbanDictionary. CoRR abs/1606.08270 (2016) - 2015
- [c3]Naomi Saphra, Adam Lopez:
AMRICA: an AMR Inspector for Cross-language Alignments. HLT-NAACL 2015: 36-40 - 2014
- [c2]Andrea Vedaldi, Siddharth Mahendran, Stavros Tsogkas, Subhransu Maji, Ross B. Girshick, Juho Kannala, Esa Rahtu, Iasonas Kokkinos, Matthew B. Blaschko, David J. Weiss, Ben Taskar, Karen Simonyan, Naomi Saphra, Sammy Mohamed:
Understanding Objects in Detail with Fine-Grained Attributes. CVPR 2014: 3622-3629 - 2013
- [c1]Nathan Schneider, Brendan O'Connor, Naomi Saphra, David Bamman, Manaal Faruqui, Noah A. Smith, Chris Dyer, Jason Baldridge:
A Framework for (Under)specifying Dependency Syntax without Overloading Annotators. LAW@ACL 2013: 51-60 - [i1]Nathan Schneider, Brendan O'Connor, Naomi Saphra, David Bamman, Manaal Faruqui, Noah A. Smith, Chris Dyer, Jason Baldridge:
A framework for (under)specifying dependency syntax without overloading annotators. CoRR abs/1306.2091 (2013)
Coauthor Index
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last updated on 2024-11-15 20:35 CET by the dblp team
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