44 citations
- Microsoft (United States)US11 papers
- Microsoft Research (United Kingdom)GB4 papers
- Johns Hopkins UniversityUS3 papers
- Columbia UniversityUS2 papers
- Imperial College LondonGB2 papers
- Johns Hopkins University Applied Physics LaboratoryUS2 papers
- Shanghai Jiao Tong UniversityCN2 papers
- Tsinghua UniversityCN2 papers
- University of ChicagoUS2 papers
- University of Illinois Urbana-ChampaignUS2 papers
- University of WashingtonUS2 papers
- Amazon (United States)US1 paper
35 papers
Evaluating SAP RPT-1 for Enterprise Business Process Prediction: In-Context Learning vs. Traditional Machine Learning on Structured SAP Data
Amit Lal
Tabular foundation models aim to make machine learning accessible for enterprise data without task-specific training. This paper presents the first independent evaluation of SAP's…
Quantum matrix arithmetics with Hamiltonian evolution
Christopher Kang, Yuan Su
The efficient implementation of matrix arithmetic operations underpins the speedups of many quantum algorithms. We develop a suite of methods to perform matrix arithmetics -- with…
Trustful LLMs: Customizing and Grounding Text Generation with Knowledge Bases and Dual Decoders
Xiaofeng Zhu, Jaya Krishna Mandivarapu
Although people are impressed by the content generation skills of large language models, the use of LLMs, such as ChatGPT, is limited by the domain grounding of the content. The co…
Drivers of Electric Vehicle Adoption in Nigeria: An Extended UTAUT Framework Approach
Qasim Ajao, Lanre Sadeeq, Oluwatobi Oluwaponmile Sodiq
Electric vehicles (EVs) represent a significant advancement in automotive technology, utilizing electricity as a power source instead of traditional fossil fuels, while incorporati…
No-Go Theorems for Universal Entanglement Purification
Allen Zang, Xinan Chen, Eric Chitambar +2
An entanglement purification protocol (EPP) aims to transform multiple noisy entangled states into a single entangled state with higher fidelity. In this work we consider EPPs that…
Heterogeneous Graph Neural Network on Semantic Tree
Mingyu Guan, Jack W. Stokes, Qinlong Luo +4
The recent past has seen an increasing interest in Heterogeneous Graph Neural Networks (HGNNs), since many real-world graphs are heterogeneous in nature, from citation graphs to em…