# Interactive Garment Recommendation with User in the Loop

arXiv: https://arxiv.org/abs/2402.11627 · HTML: https://mlsanity.com/paper/2402.11627/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Placed in RL training of language and agent models, one of 15 directions in Deep reinforcement learning methods.
- Builds on 16 of its 48 references that are in the map.
- First posted on arXiv 18 Feb 2024.

## Placed in

- Deep reinforcement learning methods / [RL training of language and agent models](https://mlsanity.com/deeprl/rl-training-of-language-and-agent-models/)

## Builds on (most cited first, 16 of 16)

- [Learning Convolutional Neural Networks for Graphs](https://mlsanity.com/paper/1605.05273/) (2016)
- [Composing Text and Image for Image Retrieval - An Empirical Odyssey](https://mlsanity.com/paper/1812.07119/) (2018)
- [A Theoretical Analysis of Deep Q-Learning](https://mlsanity.com/paper/1901.00137/) (2019)
- [Automatic Spatially-aware Fashion Concept Discovery](https://mlsanity.com/paper/1708.01311/) (2017)
- [Dialog-based Interactive Image Retrieval](https://mlsanity.com/paper/1805.00145/) (2018)
- [Learning Fashion Compatibility with Bidirectional LSTMs](https://mlsanity.com/paper/1707.05691/) (2017)
- [Learning Type-Aware Embeddings for Fashion Compatibility](https://mlsanity.com/paper/1803.09196/) (2018)
- [Self-Supervised Reinforcement Learning for Recommender Systems](https://mlsanity.com/paper/2006.05779/) (2020)
- [Conversational Fashion Image Retrieval via Multiturn Natural Language Feedback](https://mlsanity.com/paper/2106.04128/) (2021)
- [Dressing as a Whole: Outfit Compatibility Learning Based on Node-wise Graph Neural Networks](https://mlsanity.com/paper/1902.08009/) (2019)
- [Aesthetic-based Clothing Recommendation](https://mlsanity.com/paper/1809.05822/) (2018)
- [FashionNTM: Multi-turn Fashion Image Retrieval via Cascaded Memory](https://mlsanity.com/paper/2308.10170/) (2023)
- [Garment Recommendation with Memory Augmented Neural Networks](https://mlsanity.com/paper/2012.06200/) (2020)
- [Contrastive Learning for Interactive Recommendation in Fashion](https://mlsanity.com/paper/2207.12033/) (2022)
- [Fashion Recommendation Based on Style and Social Events](https://mlsanity.com/paper/2208.00725/) (2022)
- [Transformer-based Graph Neural Networks for Outfit Generation](https://mlsanity.com/paper/2304.08098/) (2023)

## Abstract (arXiv)

Recommending fashion items often leverages rich user profiles and makes targeted suggestions based on past history and previous purchases. In this paper, we work under the assumption that no prior knowledge is given about a user. We propose to build a user profile on the fly by integrating user reactions as we recommend complementary items to compose an outfit. We present a reinforcement learning agent capable of suggesting appropriate garments and ingesting user feedback so to improve its recommendations and maximize user satisfaction. To train such a model, we resort to a proxy model to be able to simulate having user feedback in the training loop. We experiment on the IQON3000 fashion dataset and we find that a reinforcement learning-based agent becomes capable of improving its recommendations by taking into account personal preferences. Furthermore, such task demonstrated to be hard for non-reinforcement models, that cannot exploit exploration during training.