Zobrazeno 1 - 10
of 74
pro vyhledávání: '"Song Yuanfeng"'
Reliable responses of service chatbots are often achieved by employing retrieval-based methods that restrict answers to a knowledge base comprising predefined question-answer pairs (QA pairs). To accommodate potential variations in how a customer's q
Externí odkaz:
http://arxiv.org/abs/2410.12444
Autor:
Li, Shuaimin, Song, Yuanfeng, Chen, Xuanang, Peng, Anni, Wan, Zhuoyue, Zhang, Chen Jason, Wong, Raymond Chi-Wing
Text-to-visualization (text-to-vis) models have become valuable tools in the era of big data, enabling users to generate data visualizations and make informed decisions through natural language queries (NLQs). Despite their widespread application, th
Externí odkaz:
http://arxiv.org/abs/2410.06782
With the growing importance of customer service in contemporary business, recognizing the intents behind service dialogues has become essential for the strategic success of enterprises. However, the nature of dialogue data varies significantly across
Externí odkaz:
http://arxiv.org/abs/2410.06190
Understanding the meaning of infant cries is a significant challenge for young parents in caring for their newborns. The presence of background noise and the lack of labeled data present practical challenges in developing systems that can detect cryi
Externí odkaz:
http://arxiv.org/abs/2409.19689
Data visualization (DV) is the fundamental and premise tool to improve the efficiency in conveying the insights behind the big data, which has been widely accepted in existing data-driven world. Task automation in DV, such as converting natural langu
Externí odkaz:
http://arxiv.org/abs/2408.07401
Autor:
Fan, Tao, Kang, Yan, Chen, Weijing, Gu, Hanlin, Song, Yuanfeng, Fan, Lixin, Chen, Kai, Yang, Qiang
In the context of real-world applications, leveraging large language models (LLMs) for domain-specific tasks often faces two major challenges: domain-specific knowledge privacy and constrained resources. To address these issues, we propose PDSS, a pr
Externí odkaz:
http://arxiv.org/abs/2406.12403
Autor:
Fan, Tao, Ma, Guoqiang, Kang, Yan, Gu, Hanlin, Song, Yuanfeng, Fan, Lixin, Chen, Kai, Yang, Qiang
Recent research in federated large language models (LLMs) has primarily focused on enabling clients to fine-tune their locally deployed homogeneous LLMs collaboratively or on transferring knowledge from server-based LLMs to small language models (SLM
Externí odkaz:
http://arxiv.org/abs/2406.02224
Text-to-Vis is an emerging task in the natural language processing (NLP) area that aims to automatically generate data visualizations from natural language questions (NLQs). Despite their progress, existing text-to-vis models often heavily rely on le
Externí odkaz:
http://arxiv.org/abs/2404.07135
Entity resolution, which involves identifying and merging records that refer to the same real-world entity, is a crucial task in areas like Web data integration. This importance is underscored by the presence of numerous duplicated and multi-version
Externí odkaz:
http://arxiv.org/abs/2403.06434
Data visualization (DV) systems are increasingly recognized for their profound capability to uncover insights from vast datasets, gaining attention across both industry and academia. Crafting data queries is an essential process within certain declar
Externí odkaz:
http://arxiv.org/abs/2402.07909