Zobrazeno 1 - 10
of 252
pro vyhledávání: '"Zhu, Hengshu"'
Visual geo-localization demands in-depth knowledge and advanced reasoning skills to associate images with real-world geographic locations precisely. In general, traditional methods based on data-matching are hindered by the impracticality of storing
Externí odkaz:
http://arxiv.org/abs/2408.11312
Reciprocal recommender systems~(RRS), conducting bilateral recommendations between two involved parties, have gained increasing attention for enhancing matching efficiency. However, the majority of existing methods in the literature still reuse conve
Externí odkaz:
http://arxiv.org/abs/2408.09748
In this paper, we present the technical details and periodic findings of our project, CareerAgent, which aims to build a generative simulation framework for a Holacracy organization using Large Language Model-based Autonomous Agents. Specifically, th
Externí odkaz:
http://arxiv.org/abs/2408.11826
Recent advancements in Large Language Models (LLMs) have significantly extended their capabilities, evolving from basic text generation to complex, human-like interactions. In light of the possibilities that LLMs could assume significant workplace re
Externí odkaz:
http://arxiv.org/abs/2407.08564
Many studies have revealed that large language models (LLMs) exhibit uneven awareness of different contextual positions.Their limited context awareness can lead to overlooking critical information and subsequent task failures. While several approache
Externí odkaz:
http://arxiv.org/abs/2406.19598
Job recommender systems are crucial for aligning job opportunities with job-seekers in online job-seeking. However, users tend to adjust their job preferences to secure employment opportunities continually, which limits the performance of job recomme
Externí odkaz:
http://arxiv.org/abs/2407.00082
Autor:
Yu, Xiaoshan, Qin, Chuan, Shen, Dazhong, Yang, Shangshang, Ma, Haiping, Zhu, Hengshu, Zhang, Xingyi
In the realm of education, both independent learning and group learning are esteemed as the most classic paradigms. The former allows learners to self-direct their studies, while the latter is typically characterized by teacher-directed scenarios. Re
Externí odkaz:
http://arxiv.org/abs/2406.12465
Autor:
Chen, Xi, Qin, Chuan, Fang, Chuyu, Wang, Chao, Zhu, Chen, Zhuang, Fuzhen, Zhu, Hengshu, Xiong, Hui
In a rapidly evolving job market, skill demand forecasting is crucial as it enables policymakers and businesses to anticipate and adapt to changes, ensuring that workforce skills align with market needs, thereby enhancing productivity and competitive
Externí odkaz:
http://arxiv.org/abs/2406.11920
This paper explores the evolution of occupations within the context of industry and technology life cycles, highlighting the critical yet underexplored intersection between occupational trends and broader economic dynamics. Introducing the Occupation
Externí odkaz:
http://arxiv.org/abs/2406.15373
Autor:
Jiang, Feihu, Qin, Chuan, Zhang, Jingshuai, Yao, Kaichun, Chen, Xi, Shen, Dazhong, Zhu, Chen, Zhu, Hengshu, Xiong, Hui
In the contemporary era of widespread online recruitment, resume understanding has been widely acknowledged as a fundamental and crucial task, which aims to extract structured information from resume documents automatically. Compared to the tradition
Externí odkaz:
http://arxiv.org/abs/2404.13067