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Found 10 papers, 3 papers with code
FTII-Bench: A Comprehensive Multimodal Benchmark for Flow Text with Image Insertion
Based on this, we introduce the Flow Text with Image Insertion Benchmark (FTII-Bench), which includes 318 high-quality Chinese image-text news articles and 307 high-quality English image-text news articles, covering 10 different news domains.
MM-CamObj: A Comprehensive Multimodal Dataset for Camouflaged Object Scenarios
CamObj-Instruct is collected for fine-tuning the LVLMs with improved instruction-following capabilities, and it includes 11, 363 images and 68, 849 conversations with diverse instructions.
$\text{Memory}^3$: Language Modeling with Explicit Memory
The model is named $\text{Memory}^3$, since explicit memory is the third form of memory in LLMs after implicit memory (model parameters) and working memory (context key-values).
Similar Scenes arouse Similar Emotions: Parallel Data Augmentation for Stylized Image Captioning
Second, we construct the plugable multi-modal scene retriever to retrieve scenes represented with pairs of an image and its stylized caption, which are similar to the query image or caption in the large-scale factual data.
Dialogue State Tracking with Multi-Level Fusion of Predicted Dialogue States and Conversations
Then the representation of each dialogue turn is aggregated by a hierarchical structure to form the passage information, which is utilized in the current turn of DST.
Predict-then-Decide: A Predictive Approach for Wait or Answer Task in Dialogue Systems
More specifically, we take advantage of a decision model to help the dialogue system decide whether to wait or answer.
MTSS: Learn from Multiple Domain Teachers and Become a Multi-domain Dialogue Expert
How to build a high-quality multi-domain dialogue system is a challenging work due to its complicated and entangled dialogue state space among each domain, which seriously limits the quality of dialogue policy, and further affects the generated response.
"Wait, I'm Still Talking!" Predicting the Dialogue Interaction Behavior Using Imagine-Then-Arbitrate Model
And the arbitrator decides whether to wait or to make a response to the user directly.
Task-Oriented Conversation Generation Using Heterogeneous Memory Networks
How to incorporate external knowledge into a neural dialogue model is critically important for dialogue systems to behave like real humans.
Teacher-Student Framework Enhanced Multi-domain Dialogue Generation
Dialogue systems dealing with multi-domain tasks are highly required.
