3.2k citations · 8.8k across the 71 of their papers we have counts for
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Sorting Out Quantum Monte Carlo
Jack Richter-Powell, Luca Thiede, Alán Asparu-Guzik +1
Molecular modeling at the quantum level requires choosing a parameterization of the wavefunction that both respects the required particle symmetries, and is scalable to systems of…
Towards Understanding Sycophancy in Language Models
Mrinank Sharma, Meg Tong, Tomasz Korbak +16
Human feedback is commonly utilized to finetune AI assistants. But human feedback may also encourage model responses that match user beliefs over truthful ones, a behaviour known a…
Tools for Verifying Neural Models' Training Data
Dami Choi, Yonadav Shavit, David Duvenaud
It is important that consumers and regulators can verify the provenance of large neural models to evaluate their capabilities and risks. We introduce the concept of a "Proof-of-Tra…