Abstract Information that can encapsulate a person's daily life and its different aspects
provides insightful knowledge. This knowledge can prove to be more useful than general …

Relation extraction (RE) is an essential topic in natural language processing and has
attracted extensive attention. Current RE approaches achieve fantastic results on common …

Making machines endowed with eyes and brains to effectively understand and analyze
crowd scenes is of paramount importance for building a smart city to serve people. This is of …

Multi-party multi-turn dialogue comprehension brings unprecedented challenges in handling
complicated scenarios, as the co-occurrence of multiple speakers causes complexity and …

Automatically extracted interpersonal relationships of conversation interlocutors can enrich
personal knowledge bases to enhance personalized search, recommenders and chatbots …

Recently, there have merged a class of task-oriented dialogue (TOD) datasets collected
through Wizard-of-Oz simulated games. However, the Wizard-of-Oz data are in fact …

Large language models (LLMs) have achieved remarkable breakthroughs in new dialogue
capabilities, refreshing human's impressions on dialogue systems. The long-standing goal …

Social relationships play a crucial role in shaping daily conversations and information
sharing within social networks, both in person and on online platforms like Twitter and …

Crowd scenes analysis plays an important role in various fields, including public security,
smart cities, and intelligent transportation systems. However, traditional crowd scenes …

As language models are often deployed as chatbot assistants, it becomes a virtue for
models to engage in conversations in a user's first language. While these models are trained …