# ModelPS: An Interactive and Collaborative Platform for Editing Pre-trained Models at Scale

arXiv: https://arxiv.org/abs/2105.08275 · HTML: https://mlsanity.com/paper/2105.08275/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 24 references that are in the map.
- First posted on arXiv 18 May 2021.

## Builds on (most cited first, 10 of 10)

- [Distilling the Knowledge in a Neural Network](https://mlsanity.com/paper/1503.02531/) (2015)
- [Learning Transferable Features with Deep Adaptation Networks](https://mlsanity.com/paper/1502.02791/) (2015)
- [LayoutLM: Pre-training of Text and Layout for Document Image Understanding](https://mlsanity.com/paper/1912.13318/) (2019)
- [Clipper: A Low-Latency Online Prediction Serving System](https://mlsanity.com/paper/1612.03079/) (2016)
- [LogME: Practical Assessment of Pre-trained Models for Transfer Learning](https://mlsanity.com/paper/2102.11005/) (2021)
- [Applying Deep Learning To Airbnb Search](https://mlsanity.com/paper/1810.09591/) (2018)
- [MLModelCI: An Automatic Cloud Platform for Efficient MLaaS](https://mlsanity.com/paper/2006.05096/) (2020)
- [EasyTransfer -- A Simple and Scalable Deep Transfer Learning Platform for NLP Applications](https://mlsanity.com/paper/2011.09463/) (2020)
- [Hysia: Serving DNN-Based Video-to-Retail Applications in Cloud](https://mlsanity.com/paper/2006.05117/) (2020)
- [InferBench: Understanding Deep Learning Inference Serving with an Automatic Benchmarking System](https://mlsanity.com/paper/2011.02327/) (2020)

## Built on by (most cited first, 2 of 2)

- [Rainbow Keywords: Efficient Incremental Learning for Online Spoken Keyword Spotting](https://mlsanity.com/paper/2203.16361/) (2022)
- [DataCI: A Platform for Data-Centric AI on Streaming Data](https://mlsanity.com/paper/2306.15538/) (2023)

## Abstract (arXiv)

AI engineering has emerged as a crucial discipline to democratize deep neural network (DNN) models among software developers with a diverse background. In particular, altering these DNN models in the deployment stage posits a tremendous challenge. In this research, we propose and develop a low-code solution, ModelPS (an acronym for "Model Photoshop"), to enable and empower collaborative DNN model editing and intelligent model serving. The ModelPS solution embodies two transformative features: 1) a user-friendly web interface for a developer team to share and edit DNN models pictorially, in a low-code fashion, and 2) a model genie engine in the backend to aid developers in customizing model editing configurations for given deployment requirements or constraints. Our case studies with a wide range of deep learning (DL) models show that the system can tremendously reduce both development and communication overheads with improved productivity.