635 citations · 1.7k across the 22 of their papers we have counts for
23 papers
Balancing Knowledge Delivery and Emotional Comfort in Healthcare Conversational Systems
Shang-Chi Tsai, Yun-Nung Chen
With the advancement of large language models, many dialogue systems are now capable of providing reasonable and informative responses to patients' medical conditions. However, whe…
FinanceReasoning: Benchmarking Financial Numerical Reasoning More Credible, Comprehensive and Challenging
Zichen Tang, Haihong E, Ziyan Ma +10
We introduce FinanceReasoning, a novel benchmark designed to evaluate the reasoning capabilities of large reasoning models (LRMs) in financial numerical reasoning problems. Compare…
GPT-4o System Card
OpenAI, :, Aaron Hurst +416
GPT-4o is an autoregressive omni model that accepts as input any combination of text, audio, image, and video, and generates any combination of text, audio, and image outputs. It's…
VISTA: A Visual and Textual Attention Dataset for Interpreting Multimodal Models
Harshit, Tolga Tasdizen
The recent developments in deep learning led to the integration of natural language processing (NLP) with computer vision, resulting in powerful integrated Vision and Language Mode…
Strongly Anisotropic Spin and Orbital Rashba Effect at a Tellurium - Noble Metal Interface
B. Geldiyev, M. Ünzelmann, P. Eck +19
We study the interplay of lattice, spin and orbital degrees of freedom in a two-dimensional model system: a flat square lattice of Te atoms on a Au(100) surface. The atomic structu…
GPT-4 Technical Report
OpenAI, Josh Achiam, Steven Adler +278
We report the development of GPT-4, a large-scale, multimodal model which can accept image and text inputs and produce text outputs. While less capable than humans in many real-wor…
A Note on Noisy Reservoir Computation
Anthony M. Polloreno, Reuben R. W. Wang, Nikolas A. Tezak
In this note we extend the definition of the Information Processing Capacity (IPC) by Dambre et al [1] to include the effects of stochastic reservoir dynamics. We quantify the degr…
Efficient Training of Language Models to Fill in the Middle
Mohammad Bavarian, Heewoo Jun, Nikolas Tezak +4
We show that autoregressive language models can learn to infill text after we apply a straightforward transformation to the dataset, which simply moves a span of text from the midd…
Text and Code Embeddings by Contrastive Pre-Training
Arvind Neelakantan, Tao Xu, Raul Puri +22
Text embeddings are useful features in many applications such as semantic search and computing text similarity. Previous work typically trains models customized for different use c…
A quantum-classical cloud platform optimized for variational hybrid algorithms
Peter J. Karalekas, Nikolas A. Tezak, Eric C. Peterson +3
In order to support near-term applications of quantum computing, a new compute paradigm has emerged--the quantum-classical cloud--in which quantum computers (QPUs) work in tandem w…
Solving Rubik's Cube with a Robot Hand
OpenAI, Ilge Akkaya, Marcin Andrychowicz +16
We demonstrate that models trained only in simulation can be used to solve a manipulation problem of unprecedented complexity on a real robot. This is made possible by two key comp…
Quantum Kitchen Sinks: An algorithm for machine learning on near-term quantum computers
C. M. Wilson, J. S. Otterbach, N. Tezak +7
Noisy intermediate-scale quantum computing devices are an exciting platform for the exploration of the power of near-term quantum applications. Performing nontrivial tasks in such…
Unsupervised Machine Learning on a Hybrid Quantum Computer
J. S. Otterbach, R. Manenti, N. Alidoust +27
Machine learning techniques have led to broad adoption of a statistical model of computing. The statistical distributions natively available on quantum processors are a superset of…
Demonstration of Universal Parametric Entangling Gates on a Multi-Qubit Lattice
M. Reagor, C. B. Osborn, N. Tezak +56
We show that parametric coupling techniques can be used to generate selective entangling interactions for multi-qubit processors. By inducing coherent population exchange between a…
Low dimensional manifolds for exact representation of open quantum systems
Nikolas Tezak, Nina Hadis Amini, Hideo Mabuchi
Weakly nonlinear degrees of freedom in dissipative quantum systems tend to localize near manifolds of quasi-classical states. We present a family of analytical and computational me…
All-mechanical quantum noise cancellation for accelerometry: broadband with momentum measurements, narrow band without
Kurt Jacobs, Nikolas Tezak, Hideo Mabuchi +1
We show that the ability to make direct measurements of momentum, in addition to the usual direct measurements of position, allows a simple configuration of two identical mechanica…
A Coherent Perceptron for All-Optical Learning
Nikolas Tezak, Hideo Mabuchi
We present nonlinear photonic circuit models for constructing programmable linear transformations and use these to realize a coherent Perceptron, i.e., an all-optical linear classi…
Quantum noise in large-scale coherent nonlinear photonic circuits
Charles Santori, Jason S. Pelc, Raymond G. Beausoleil +3
A semiclassical simulation approach is presented for studying quantum noise in large-scale photonic circuits incorporating an ideal Kerr nonlinearity. A circuit solver is used to g…
Squeezed light in an optical parametric oscillator network with coherent feedback quantum control
Orion Crisafulli, Nikolas Tezak, Daniel B. S. Soh +2
We present squeezing and anti-squeezing spectra of the output from a degenerate optical parametric oscillator (OPO) network arranged in different coherent quantum feedback configur…
Transformation of quantum photonic circuit models by term rewriting
Gopal Sarma, Ryan Hamerly, Nikolas Tezak +2
The development of practical methods for synthesis and verification of complex photonic circuits presents a grand challenge for the nascent field of quantum engineering. Of course,…
Specification of photonic circuits using Quantum Hardware Description Language
Nikolas Tezak, Armand Niederberger, Dmitri S. Pavlichin +2
Following the simple observation that the interconnection of a set of quantum optical input-output devices can be specified using structural mode VHSIC Hardware Description Languag…
Rydberg-Rydberg interaction profile from the excitation dynamics of ultracold atoms in lattices
Michael Mayle, Wolfgang Zeller, Nikolas Tezak +1
We propose a method for the determination of the interaction potential of Rydberg atoms. Specifically, we consider a laser-driven Rydberg gas confined in a one-dimensional lattice…
Spectral properties of finite laser-driven lattices of ultracold Rydberg atoms
Nikolas Tezak, Michael Mayle, Peter Schmelcher
We investigate the spectral properties of a finite laser-driven lattice of ultracold Rydberg atoms exploiting the dipole blockade effect in the frozen Rydberg gas regime. Uniform o…