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Alex Mallen
Alex Mallen
EleutherAI
Verified email at uw.edu - Homepage
Title
Cited by
Cited by
Year
When not to trust language models: Investigating effectiveness of parametric and non-parametric memories
A Mallen, A Asai, V Zhong, R Das, D Khashabi, H Hajishirzi
arXiv preprint arXiv:2212.10511, 2022
1262022
When not to trust language models: Investigating effectiveness and limitations of parametric and non-parametric memories
A Mallen, A Asai, V Zhong, R Das, H Hajishirzi, D Khashabi
arXiv preprint arXiv:2212.10511 7, 2022
712022
Representation engineering: A top-down approach to ai transparency
A Zou, L Phan, S Chen, J Campbell, P Guo, R Ren, A Pan, X Yin, ...
arXiv preprint arXiv:2310.01405, 2023
642023
Representation Engineering: A Top-Down Approach to AI Transparency, October 2023
A Zou, L Phan, S Chen, J Campbell, P Guo, R Ren, A Pan, X Yin, ...
URL http://arxiv. org/abs/2310.01405, 0
7
Deep probabilistic Koopman: long-term time-series forecasting under periodic uncertainties
AT Mallen, H Lange, JN Kutz
International Journal of Forecasting, 2023
42023
Neural Networks Learn Statistics of Increasing Complexity
N Belrose, Q Pope, L Quirke, A Mallen, X Fern
arXiv preprint arXiv:2402.04362, 2024
12024
Eliciting Latent Knowledge from Quirky Language Models
A Mallen, N Belrose
arXiv preprint arXiv:2312.01037, 2023
12023
The Synaptic Architecture of Layer 5 Thick Tufted Excitatory Neurons in the Visual Cortex of Mice
AL Bodor, CM Schneider-Mizell, C Zhang, L Elabbady, A Mallen, ...
bioRxiv, 2023.10. 18.562531, 2023
12023
Enhancing Neural Network Transparency through Representation Analysis
A Zou, L Phan, SL Chen, J Campbell, PH Guo, R Ren, A Pan, X Yin, ...
2023
Koopman-inspired approach for identification of exogenous anomalies in nonstationary time-series data
A Mallen, CA Keller, JN Kutz
Machine Learning: Science and Technology 4 (2), 025033, 2023
2023
Robust Unsupervised Mining of Dense Sub-Graphs at Multiple Resolutions
N Gupta, G Gupta, J Ghosh, S Shankar, A Mallen
2020
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Articles 1–11