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Yann Dubois
Yann Dubois
PhD, Stanford University
Adresse e-mail validée de stanford.edu - Page d'accueil
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Stanford alpaca: An instruction-following llama model
R Taori*, I Gulrajani*, T Zhang*, Y Dubois*, X Li*, C Guestrin, P Liang, ...
2216*2023
AlpacaEval: An automatic evaluator of instruction-following models
X Li*, T Zhang*, Y Dubois*, R Taori*, I Gulrajani, C Guestrin, P Liang, ...
3032023
AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback
Y Dubois*, X Li*, R Taori*, T Zhang*, I Gulrajani, J Ba, C Guestrin, P Liang, ...
NeurIPS, 2023
2792023
Convolutional Conditional Neural Processes
J Gordon, WP Bruinsma, AYK Foong, J Requeima, Y Dubois, RE Turner
ICLR, 2020
1662020
Optimal Representations for Covariate Shifts
Y Ruan*, Y Dubois*, CJ Maddison
ICLR, 2021
74*2021
Lossy Compression for Lossless Prediction
Y Dubois, B Bloem-Reddy, K Ullrich, CJ Maddison
NeurIPS, 2021
722021
Meta-Learning Stationary Stochastic Process Prediction with Convolutional Neural Processes
AYK Foong, WP Bruinsma, J Gordon, Y Dubois, J Requeima, RE Turner
NeurIPS, 2020
672020
Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators
Y Dubois, B Galambosi, P Liang, TB Hashimoto
COLM, 2024
612024
Is a Caption Worth a Thousand Images? A Controlled Study for Representation Learning
S Santurkar, Y Dubois, R Taori, P Liang, T Hashimoto
ICLR, 2022
46*2022
Learning Optimal Representations with the Decodable Information Bottleneck
Y Dubois, D Kiela, DJ Schwab, R Vedantam
NeurIPS, 2020
402020
Identifying the Risks of LM Agents with an LM-Emulated Sandbox
Y Ruan, H Dong, A Wang, S Pitis, Y Zhou, J Ba, Y Dubois, CJ Maddison, ...
ICLR, 2023
362023
Improving Self-Supervised Learning by Characterizing Idealized Representations
Y Dubois, T Hashimoto, S Ermon, P Liang
NeurIPS, 2022
352022
Location Attention for Extrapolation to Longer Sequences
Y Dubois, G Dagan, D Hupkes, E Bruni
ACL, 2019
352019
Learning Instance-Specific Augmentations by Capturing Local Invariances
N Miao, T Rainforth, E Mathieu, Y Dubois, YW Teh, A Foster, H Kim
ICML, 2022
13*2022
Evaluating Self-Supervised Learning via Risk Decomposition
Y Dubois, T Hashimoto, P Liang
ICML, 2023
62023
Learning to (Learn at Test Time): RNNs with Expressive Hidden States
Y Sun, X Li, K Dalal, J Xu, A Vikram, G Zhang, Y Dubois, X Chen, X Wang, ...
arXiv preprint arXiv:2407.04620, 2024
52024
Neural process family
Y Dubois, J Gordon, AY Foong
yanndubs.github.io/Neural-Process-Family, 2020
2020
Revisiting Associative Compression: I Can’t Believe It’s Not Better
W Xu, MJ Muckley, Y Dubois, K Ullrich
Conditional Neural Processes for Semi-Supervised Learning
Y Dubois, RE Turner
Understanding Disentangling in VAE
Y Dubois, A Kastanos, D Lines, B Melman
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