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Found 6 papers, 0 papers with code
Generation and Extraction Combined Dialogue State Tracking with Hierarchical Ontology Integration
Recently, the focus of dialogue state tracking has expanded from single domain to multiple domains.
DAP: Domain-aware Prompt Learning for Vision-and-Language Navigation
Then we introduce soft visual prompts in the input space of the visual encoder in a pretrained model.
Prompt-based Context- and Domain-aware Pretraining for Vision and Language Navigation
In the indoor-aware stage, we apply an efficient tuning paradigm to learn deep visual prompts from an indoor dataset, in order to augment pretrained models with inductive biases towards indoor environments.
Visual Prompt Based Personalized Federated Learning
Then, the local model is trained on the input composed of raw data and a visual prompt to learn the distribution information contained in the prompt.
Vision-Language Navigation: A Survey and Taxonomy
This paper provides a comprehensive survey and an insightful taxonomy of these tasks based on the different characteristics of language instructions in these tasks.
How to Evaluate Your Dialogue Models: A Review of Approaches
Evaluating the quality of a dialogue system is an understudied problem.
