Publications (13)
Improved Quantum Computation using Operator Backpropagation
Bryce Fuller, Minh C. Tran, Danylo Lykov +10
Decoherence of quantum hardware is currently limiting its practical applications. At the same time, classical algorithms for simulating quantum circuits have progressed substantial…
Reasoning with Latent Tokens in Diffusion Language Models
Andre He, Sean Welleck, Daniel Fried
Discrete diffusion models have recently become competitive with autoregressive models for language modeling, even outperforming them on reasoning tasks requiring planning and globa…
Mitigating depolarizing noise on quantum computers with noise-estimation circuits
Miroslav Urbanek, Benjamin Nachman, Vincent R. Pascuzzi +3
A significant problem for current quantum computers is noise. While there are many distinct noise channels, the depolarizing noise model often appropriately describes average noise…
BridgeData V2: A Dataset for Robot Learning at Scale
Homer Walke, Kevin Black, Abraham Lee +11
We introduce BridgeData V2, a large and diverse dataset of robotic manipulation behaviors designed to facilitate research on scalable robot learning. BridgeData V2 contains 60,096…
Resource Efficient Zero Noise Extrapolation with Identity Insertions
Andre He, Benjamin Nachman, Wibe A. de Jong +1
In addition to readout errors, two-qubit gate noise is the main challenge for complex quantum algorithms on noisy intermediate-scale quantum (NISQ) computers. These errors are a si…
Goal Representations for Instruction Following: A Semi-Supervised Language Interface to Control
Vivek Myers, Andre He, Kuan Fang +7
Our goal is for robots to follow natural language instructions like "put the towel next to the microwave." But getting large amounts of labeled data, i.e. data that contains demons…
Dynamical simulations of many-body quantum chaos on a quantum computer
Laurin E. Fischer, Matea Leahy, Andrew Eddins +16
Quantum circuits with local unitaries have emerged as a rich playground for the exploration of many-body quantum dynamics of discrete-time systems. While the intrinsic locality mak…
Neural Unsupervised Reconstruction of Protolanguage Word Forms
Andre He, Nicholas Tomlin, Dan Klein
We present a state-of-the-art neural approach to the unsupervised reconstruction of ancient word forms. Previous work in this domain used expectation-maximization to predict simple…
Computationally Efficient Zero Noise Extrapolation for Quantum Gate Error Mitigation
Vincent R. Pascuzzi, Andre He, Christian W. Bauer +2
Zero noise extrapolation (ZNE) is a widely used technique for gate error mitigation on near term quantum computers because it can be implemented in software and does not require kn…
Understanding Game-Playing Agents with Natural Language Annotations
Nicholas Tomlin, Andre He, Dan Klein
We present a new dataset containing 10K human-annotated games of Go and show how these natural language annotations can be used as a tool for model interpretability. Given a board…
Rewarding the Unlikely: Lifting GRPO Beyond Distribution Sharpening
Andre He, Daniel Fried, Sean Welleck
Reinforcement learning is emerging as a primary driver for improving language model reasoning capabilities. A fundamental question is whether current reinforcement learning algorit…
ReSyn: Autonomously Scaling Synthetic Environments for Reasoning Models
Andre He, Nathaniel Weir, Kaj Bostrom +4
Reinforcement learning with verifiable rewards (RLVR) has emerged as a promising approach for training reasoning language models (RLMs) by leveraging supervision from verifiers. Al…
Disambiguating Pauli noise in quantum computers
Edward H. Chen, Senrui Chen, Laurin E. Fischer +7
To successfully perform quantum computations, it is often necessary to first accurately characterize the noise in the underlying hardware. However, it is well known that fundamenta…