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Found 9 papers, 5 papers with code
A Large-Scale Dataset for Empathetic Response Generation
Recent development in NLP shows a strong trend towards refining pre-trained models with a domain-specific dataset.
This joke is [MASK]: Recognizing Humor and Offense with Prompting
Humor is a magnetic component in everyday human interactions and communications.
AFEC: A Knowledge Graph Capturing Social Intelligence in Casual Conversations
The knowledge captured in this graph bears potential for conversational systems to understand how people offer acknowledgement, consoling, and a wide range of empathetic responses in social conversations.
Natural Language Processing with Commonsense Knowledge: A Survey
Commonsense knowledge is essential for advancing natural language processing (NLP) by enabling models to engage in human-like reasoning, which requires a deeper understanding of context and often involves making inferences based on implicit external knowledge.
HumorHunter at SemEval-2021 Task 7: Humor and Offense Recognition with Disentangled Attention
The task aims at predicting whether the given text is humorous, the average humor rating given by the annotators, and whether the humor rating is controversial.
Empathetic Dialog Generation with Fine-Grained Intents
Empathetic dialog generation aims at generating coherent responses following previous dialog turns and, more importantly, showing a sense of caring and a desire to help.
Fine-grained Emotion and Intent Learning in Movie Dialogues
We propose a novel large-scale emotional dialogue dataset, consisting of 1M dialogues retrieved from the OpenSubtitles corpus and annotated with 32 emotions and 9 empathetic response intents using a BERT-based fine-grained dialogue emotion classifier.
Uncertainty and Surprisal Jointly Deliver the Punchline: Exploiting Incongruity-Based Features for Humor Recognition
Humor recognition has been widely studied as a text classification problem using data-driven approaches.
