1.3k citations · 2.6k across the 25 of their papers we have counts for
27 papers
A robust association between LLM use and scientific productivity: Assessing stopping-time selection
Keigo Kusumegi, Xinyu Yang, Paul Ginsparg +3
Renault, Bergeaud, and Bosquet (hereafter RBB) argue that dating LLM adoption as the first month in which an author's abstract is flagged induces a stopping-time selection that can…
LLM hallucinations in the wild: Large-scale evidence from non-existent citations
Zhenyue Zhao, Yihe Wang, Toby Stuart +3
Large language models (LLMs) are known to generate plausible but false information across a wide range of contexts, yet the real-world magnitude and consequences of this hallucinat…
Scientific production in the era of Large Language Models
Keigo Kusumegi, Xinyu Yang, Paul Ginsparg +3
Large Language Models (LLMs) are rapidly reshaping scientific research. We analyze these changes in multiple, large-scale datasets with 2.1M preprints, 28K peer review reports, and…
Process Tomography for Clifford Unitaries
Timothy Skaras, Paul Ginsparg
We present an algorithm for performing quantum process tomography on an unknown -qubit unitary from the Clifford group. Our algorithm uses Bell basis measurements to determi…
Experimental error mitigation using linear rescaling for variational quantum eigensolving with up to 20 qubits
Eliott Rosenberg, Paul Ginsparg, Peter L. McMahon
Quantum computers have the potential to help solve a range of physics and chemistry problems, but noise in quantum hardware currently limits our ability to obtain accurate results…
Attention-based Quantum Tomography
Peter Cha, Paul Ginsparg, Felix Wu +3
With rapid progress across platforms for quantum systems, the problem of many-body quantum state reconstruction for noisy quantum states becomes an important challenge. Recent work…