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Found 6 papers, 3 papers with code
Multi-linguality helps: Event-Argument Extraction for Disaster Domain in Cross-lingual and Multi-lingual setting
Extracting related arguments like Time, Place, Casualties, etc., provides a complete picture of the disaster event.
Distraction-free Embeddings for Robust VQA
The generation of effective latent representations and their subsequent refinement to incorporate precise information is an essential prerequisite for Vision-Language Understanding (VLU) tasks such as Video Question Answering (VQA).
CDialog: A Multi-turn Covid-19 Conversation Dataset for Entity-Aware Dialog Generation
The development of conversational agents to interact with patients and deliver clinical advice has attracted the interest of many researchers, particularly in light of the COVID-19 pandemic.
Commonsense and Named Entity Aware Knowledge Grounded Dialogue Generation
In this paper, we present a novel open-domain dialogue generation model which effectively utilizes the large-scale commonsense and named entity based knowledge in addition to the unstructured topic-specific knowledge associated with each utterance.
Modelling Context Emotions using Multi-task Learning for Emotion Controlled Dialog Generation
We employ multi-task learning to predict the emotion label and to generate a viable response for a given utterance using a common encoder with multiple decoders.
