Results 11 to 20 of about 6,611,777 (348)
Weighted programming: a programming paradigm for specifying mathematical models [PDF]
Proceedings of the ACM on Programming Languages, 2022 We study weighted programming, a programming paradigm for specifying mathematical models. More specifically, the weighted programs we investigate are like usual imperative programs with two additional features: (1) nondeterministic branching and (2) weighting execution traces.
Kevin Batz +4 more
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Prompt Programming for Large Language Models: Beyond the Few-Shot Paradigm [PDF]
CHI Extended Abstracts, 2021 Prevailing methods for mapping large generative language models to supervised tasks may fail to sufficiently probe models’ novel capabilities. Using GPT-3 as a case study, we show that 0-shot prompts can significantly outperform few-shot prompts.
Laria Reynolds, Kyle McDonell
semanticscholar +1 more source
Hidet: Task-Mapping Programming Paradigm for Deep Learning Tensor Programs [PDF]
International Conference on Architectural Support for Programming Languages and Operating Systems, 2022 As deep learning models nowadays are widely adopted by both cloud services and edge devices, reducing the latency of deep learning model inferences becomes crucial to provide efficient model serving. However, it is challenging to develop efficient tensor
Yaoyao Ding +5 more
semanticscholar +1 more source
Array programming with NumPy [PDF]
Nature, 2020 Array programming provides a powerful, compact and expressive syntax for accessing, manipulating and operating on data in vectors, matrices and higher-dimensional arrays. NumPy is the primary array programming library for the Python language.
Charles R. Harris +25 more
semanticscholar +1 more source
Model-based, event-driven programming paradigm for interactive web applications
SIGPLAN symposium on New ideas, new paradigms, and reflections on programming and software, 2013 Aleksandar Milićević +3 more
openalex +2 more sources
Learning difficulties of ‘object-oriented programming paradigm using Java’: students’ perspective
, 2011 Java programming is popular both in Academia and IT Industry. Further, it is the maximum usage of programming across the world. There is a wide edge between industry expectations and knowledge of students in Java programming.
M. Sivasakthi
openalex +3 more sources
Applied Sciences, 2022 Brittleness plays an important role in assessing the stability of the surrounding rock mass in deep underground projects. To this end, the present study deals with developing a robust evolutionary programming paradigm known as linear genetic programming (
M. Jamei +5 more
semanticscholar +1 more source
MetaGPT: Meta Programming for Multi-Agent Collaborative Framework
arXiv.org, 2023 Recently, remarkable progress has been made in automated task-solving through the use of multi-agent driven by large language models (LLMs). However, existing LLM-based multi-agent works primarily focus on solving simple dialogue tasks, and complex tasks
Sirui Hong +11 more
semanticscholar +1 more source
A visual programming paradigm for abstract deep learning model development [PDF]
IndiaHCI, 2019 Deep learning is one of the fastest growing technologies in computer science with a plethora of applications. But this unprecedented growth has so far been limited to the consumption of deep learning experts.
Srikanth G. Tamilselvam +5 more
semanticscholar +1 more source
A Conversational Paradigm for Program Synthesis
arXiv.org, 2022 Program synthesis strives to generate a computer program as a solution to a given problem specification. We propose a conversational program synthesis approach via large language models, which addresses the challenges of searching over a vast program ...
Erik Nijkamp +7 more
semanticscholar +1 more source