27 citations · 42 across the 3 of their papers we have counts for
4 papers
GPQA: A Graduate-Level Google-Proof Q&A Benchmark
David Rein, Betty Li Hou, Asa Cooper Stickland +5
We present GPQA, a challenging dataset of 448 multiple-choice questions written by domain experts in biology, physics, and chemistry. We ensure that the questions are high-quality…
Multilingual Domain Adaptation for NMT: Decoupling Language and Domain Information with Adapters
Asa Cooper Stickland, Alexandre Bérard, Vassilina Nikoulina
Adapter layers are lightweight, learnable units inserted between transformer layers. Recent work explores using such layers for neural machine translation (NMT), to adapt pre-train…
Deep Transformers with Latent Depth
Xian Li, Asa Cooper Stickland, Yuqing Tang +1
The Transformer model has achieved state-of-the-art performance in many sequence modeling tasks. However, how to leverage model capacity with large or variable depths is still an o…
Diverse Ensembles Improve Calibration
Asa Cooper Stickland, Iain Murray
Modern deep neural networks can produce badly calibrated predictions, especially when train and test distributions are mismatched. Training an ensemble of models and averaging thei…