Zobrazeno 1 - 10
of 251
pro vyhledávání: '"Xie,Yubo"'
Humor is a magnetic component in everyday human interactions and communications. Computationally modeling humor enables NLP systems to entertain and engage with users. We investigate the effectiveness of prompting, a new transfer learning paradigm fo
Externí odkaz:
http://arxiv.org/abs/2210.13985
Autor:
Meng, Fanyuan, Zhu, Jiadong, Yao, Yuheng, Fenoaltea, Enrico Maria, Xie, Yubo, Yang, Pingle, Liu, Run-Ran, Zhang, Jianlin
The arise of disagreement is an emergent phenomenon that can be observed within a growing social group and, beyond a certain threshold, can lead to group fragmentation. To better understand how disagreement emerges, we introduce an analytically tract
Externí odkaz:
http://arxiv.org/abs/2208.00379
This paper introduces AFEC, an automatically curated knowledge graph based on people's day-to-day casual conversations. The knowledge captured in this graph bears potential for conversational systems to understand how people offer acknowledgement, co
Externí odkaz:
http://arxiv.org/abs/2205.10850
Publikováno v:
In Brain Research Bulletin 15 October 2024 217
Publikováno v:
In Journal of Cardiothoracic and Vascular Anesthesia October 2024 38(10):2287-2295
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
Externí odkaz:
http://arxiv.org/abs/2108.04674
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. Existing models either rely on pre-defined emotion labels to guide the response
Externí odkaz:
http://arxiv.org/abs/2105.06829
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
Externí odkaz:
http://arxiv.org/abs/2012.13624
Humor recognition has been widely studied as a text classification problem using data-driven approaches. However, most existing work does not examine the actual joke mechanism to understand humor. We break down any joke into two distinct components:
Externí odkaz:
http://arxiv.org/abs/2012.12007
Publikováno v:
In Neuroscience Letters 1 January 2024 818