56 citations · 89 across the 12 of their papers we have counts for
3 papers · 1 filter
Code Roulette: How Prompt Variability Affects LLM Code Generation
Andrei Paleyes, Radzim Sendyka, Diana Robinson +2
Code generation is one of the most active areas of application of Large Language Models (LLMs). While LLMs lower barriers to writing code and accelerate development process, the ov…
An Empirical Evaluation of Flow Based Programming in the Machine Learning Deployment Context
Andrei Paleyes, Christian Cabrera, Neil D. Lawrence
As use of data driven technologies spreads, software engineers are more often faced with the task of solving a business problem using data-driven methods such as machine learning (…
Towards better data discovery and collection with flow-based programming
Andrei Paleyes, Christian Cabrera, Neil D. Lawrence
Despite huge successes reported by the field of machine learning, such as voice assistants or self-driving cars, businesses still observe very high failure rate when it comes to de…