Categories: FAANG

BISCUIT: Scaffolding LLM-Generated Code with Ephemeral UIs in Computational Notebooks

This paper was accepted at IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC) 2024
Programmers frequently engage with machine learning tutorials in computational notebooks and have been adopting code generation technologies based on large language models (LLMs). However, they encounter difficulties in understanding and working with code produced by LLMs. To mitigate these challenges, we introduce a novel workflow into computational notebooks that augments LLM-based code generation with an additional ephemeral UI step, offering users UI scaffolds as an intermediate stage…
AI Generated Robotic Content

Recent Posts

Automated Feature Engineering in PyCaret

Automated feature engineering in

16 hours ago

Updating the Frontier Safety Framework

Our next iteration of the FSF sets out stronger security protocols on the path to…

16 hours ago

Adaptive Training Distributions with Scalable Online Bilevel Optimization

Large neural networks pretrained on web-scale corpora are central to modern machine learning. In this…

16 hours ago

Orchestrate seamless business systems integrations using Amazon Bedrock Agents

Generative AI has revolutionized technology through generating content and solving complex problems. To fully take…

16 hours ago

Helping our partners co-market faster with AI

At Google Cloud, we're deeply invested in making AI helpful to organizations everywhere — not…

16 hours ago

AMD’s Q4 revenue hits $7.66B, up 24% but stock falls

Advanced Micro Devices reported revenue of $7.658 billion for the fourth quarter, up 24% from…

17 hours ago