Dialogue State Tracking On Simmc2 0
Metrics
Act F1
Slot F1
Results
Performance results of various models on this benchmark
Model Name | Act F1 | Slot F1 | Paper Title | Repository |
|---|---|---|---|---|
| MTN | 93.4 | 76.7 | Multimodal Transformer Networks for End-to-End Video-Grounded Dialogue Systems | |
| BART-base | 95.2 | 82.0 | Learning to Embed Multi-Modal Contexts for Situated Conversational Agents | - |
| GPT-2 | 94.5 | 81.7 | Language Models are Unsupervised Multitask Learners | - |
| BART-large | 96.3 | 88.3 | Learning to Embed Multi-Modal Contexts for Situated Conversational Agents | - |
| PaCE | 97.1 | 87.0 | PaCE: Unified Multi-modal Dialogue Pre-training with Progressive and Compositional Experts |
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