Papers with multimodal text generation
Multitask Multimodal Prompted Training for Interactive Embodied Task Completion (2023.emnlp-main)
Copied to clipboard
Georgios Pantazopoulos, Malvina Nikandrou, Amit Parekh, Bhathiya Hemanthage, Arash Eshghi, Ioannis Konstas, Verena Rieser, Oliver Lemon, Alessandro Suglia
| Challenge: | Embodied MultiModal Agent (EMMA) is a unified encoder-decoder model that reasons over images and trajectories and casts action prediction as multimodal text generation. |
| Approach: | They propose an Embodied MultiModal Agent (EMMA) that uses a unified encoder-decoder model that reasons over images and trajectories and casts action prediction as multimodal text. |
| Outcome: | The proposed model performs on par with similar models on several VL benchmarks and sets a new state-of-the-art success rate on the Dialog-guided Task Completion (DTC) benchmark. |
CaTS-Bench: Can Language Models Describe Time Series? (2026.findings-acl)
Copied to clipboard
| Challenge: | Existing time series captioning benchmarks rely on fully synthetic or generic captions . authors propose a pipeline for generating high-fidelity synthetic captions, which is validated . |
| Approach: | They propose a benchmark for Context-aware Time Series reasoning across 11 diverse domains . they evaluate leading Vision-Language Models on their benchmark . |
| Outcome: | The proposed benchmark evaluates 1746 human-rewritten captions and shows they perform better than open-source models. |