ReDial (Recommendation Dialogues) is an annotated dataset of dialogues, where users recommend movies to each other. The dataset consists of over 10,000 conversations centered around the theme of providing movie recommendations.
Variants: ReDial
This dataset is used in 2 benchmarks:
| Task | Model | Paper | Date |
|---|---|---|---|
| Recommendation Systems | KERL | Knowledge Graphs and Pre-trained Language … | 2023-12-18 |
| Text Generation | UniCRS | Towards Unified Conversational Recommender Systems … | 2022-06-19 |
| Recommendation Systems | UniCRS | Towards Unified Conversational Recommender Systems … | 2022-06-19 |
| Recommendation Systems | UCCR | User-Centric Conversational Recommendation with Multi-Aspect … | 2022-04-20 |
| Text Generation | C2CRS | C2-CRS: Coarse-to-Fine Contrastive Learning for … | 2022-01-04 |
| Recommendation Systems | C2CRS | C2-CRS: Coarse-to-Fine Contrastive Learning for … | 2022-01-04 |
| Recommendation Systems | CR-Walker | CR-Walker: Tree-Structured Graph Reasoning and … | 2020-10-20 |
| Recommendation Systems | KGSF | Improving Conversational Recommender Systems via … | 2020-07-08 |
| Text Generation | KGSF | Improving Conversational Recommender Systems via … | 2020-07-08 |
| Text Generation | KBRD | Towards Knowledge-Based Recommender Dialog System | 2019-08-15 |
| Recommendation Systems | KBRD | Towards Knowledge-Based Recommender Dialog System | 2019-08-15 |
Recent papers with results on this dataset: