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2020 – today
- 2023
[i13]Jasmine Bayrooti, Noah D. Goodman, Alex Tamkin:
Multispectral Self-Supervised Learning with Viewmaker Networks. CoRR abs/2302.05757 (2023)- 2022
- [i12]Zhengxuan Wu, Isabel Papadimitriou, Alex Tamkin:
Oolong: Investigating What Makes Crosslingual Transfer Hard with Controlled Studies. CoRR abs/2202.12312 (2022) - [i11]Alex Tamkin, Dat Nguyen, Salil Deshpande, Jesse Mu, Noah D. Goodman:
Active Learning Helps Pretrained Models Learn the Intended Task. CoRR abs/2204.08491 (2022) - [i10]Alex Tamkin, Margalit Glasgow, Xiluo He, Noah D. Goodman:
Feature Dropout: Revisiting the Role of Augmentations in Contrastive Learning. CoRR abs/2212.08378 (2022) - [i9]Alex Tamkin, Kunal Handa, Avash Shrestha, Noah D. Goodman:
Task Ambiguity in Humans and Language Models. CoRR abs/2212.10711 (2022) - 2021
- [c7]Alex Tamkin, Mike Wu, Noah D. Goodman:
Viewmaker Networks: Learning Views for Unsupervised Representation Learning. ICLR 2021 - [c6]Alex Tamkin, Vincent Liu, Rongfei Lu, Daniel Fein, Colin Schultz, Noah D. Goodman:
DABS: a Domain-Agnostic Benchmark for Self-Supervised Learning. NeurIPS Datasets and Benchmarks 2021 - [i8]Alex Tamkin, Miles Brundage, Jack Clark, Deep Ganguli:
Understanding the Capabilities, Limitations, and Societal Impact of Large Language Models. CoRR abs/2102.02503 (2021) - [i7]Daniel Rothchild, Alex Tamkin, Julie Yu, Ujval Misra, Joseph Gonzalez:
C5T5: Controllable Generation of Organic Molecules with Transformers. CoRR abs/2108.10307 (2021) - [i6]Alex Tamkin, Vincent Liu, Rongfei Lu, Daniel Fein, Colin Schultz, Noah D. Goodman:
DABS: A Domain-Agnostic Benchmark for Self-Supervised Learning. CoRR abs/2111.12062 (2021) - [i5]Ananya Karthik, Mike Wu, Noah D. Goodman, Alex Tamkin:
Tradeoffs Between Contrastive and Supervised Learning: An Empirical Study. CoRR abs/2112.05340 (2021) - 2020
- [c5]Ramtin Keramati, Christoph Dann, Alex Tamkin, Emma Brunskill:
Being Optimistic to Be Conservative: Quickly Learning a CVaR Policy. AAAI 2020: 4436-4443 - [c4]Alex Tamkin, Trisha Singh, Davide Giovanardi, Noah D. Goodman:
Investigating Transferability in Pretrained Language Models. EMNLP (Findings) 2020: 1393-1401 - [c3]Alex Tamkin, Dan Jurafsky, Noah D. Goodman:
Language Through a Prism: A Spectral Approach for Multiscale Language Representations. NeurIPS 2020 - [i4]Alex Tamkin, Trisha Singh, Davide Giovanardi, Noah D. Goodman:
Investigating Transferability in Pretrained Language Models. CoRR abs/2004.14975 (2020) - [i3]Alex Tamkin, Mike Wu, Noah D. Goodman:
Viewmaker Networks: Learning Views for Unsupervised Representation Learning. CoRR abs/2010.07432 (2020) - [i2]Alex Tamkin, Dan Jurafsky, Noah D. Goodman:
Language Through a Prism: A Spectral Approach for Multiscale Language Representations. CoRR abs/2011.04823 (2020)
2010 – 2019
- 2019
- [c2]Jessica R. Cauchard
, Alex Tamkin, Cheng Yao Wang, Luke Vink, Michelle Park, Tommy Fang, James A. Landay:
Drone.io: A Gestural and Visual Interface for Human-Drone Interaction. HRI 2019: 153-162 - [c1]Ignacio Cases, Clemens Rosenbaum, Matthew Riemer, Atticus Geiger, Tim Klinger, Alex Tamkin, Olivia Li, Sandhini Agarwal, Joshua D. Greene, Dan Jurafsky, Christopher Potts, Lauri Karttunen:
Recursive Routing Networks: Learning to Compose Modules for Language Understanding. NAACL-HLT (1) 2019: 3631-3648 - [i1]Ramtin Keramati, Christoph Dann, Alex Tamkin, Emma Brunskill:
Being Optimistic to Be Conservative: Quickly Learning a CVaR Policy. CoRR abs/1911.01546 (2019)
Coauthor Index
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last updated on 2023-02-20 22:34 CET by the dblp team
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