Zobrazeno 1 - 10
of 3 006
pro vyhledávání: '"intent classification"'
Dialogue intent classification aims to identify the underlying purpose or intent of a user's input in a conversation. Current intent classification systems encounter considerable challenges, primarily due to the vast number of possible intents and th
Externí odkaz:
http://arxiv.org/abs/2412.15603
Autor:
Li, Yanhua, Ouyang, Xiaocao, Pan, Chaofan, Zhang, Jie, Zhao, Sen, Xia, Shuyin, Yang, Xin, Wang, Guoyin, Li, Tianrui
Publikováno v:
AAAI2025
Open intent classification is critical for the development of dialogue systems, aiming to accurately classify known intents into their corresponding classes while identifying unknown intents. Prior boundary-based methods assumed known intents fit wit
Externí odkaz:
http://arxiv.org/abs/2412.13542
Generating large-scale, domain-specific, multilingual multi-turn dialogue datasets remains a significant hurdle for training effective Multi-Turn Intent Classification models in chatbot systems. In this paper, we introduce Chain-of-Intent, a novel me
Externí odkaz:
http://arxiv.org/abs/2411.14252
Accurate multi-turn intent classification is essential for advancing conversational AI systems. However, challenges such as the scarcity of comprehensive datasets and the complexity of contextual dependencies across dialogue turns hinder progress. Th
Externí odkaz:
http://arxiv.org/abs/2411.12307
Conversational systems have a Natural Language Understanding (NLU) module. In this module, there is a task known as an intent classification that aims at identifying what a user is attempting to achieve from an utterance. Previous works use only the
Externí odkaz:
http://arxiv.org/abs/2411.06022
In virtual assistant (VA) systems it is important to reject or redirect user queries that fall outside the scope of the system. One of the most accurate approaches for out-of-scope (OOS) rejection is to combine it with the task of intent classificati
Externí odkaz:
http://arxiv.org/abs/2410.13649
Autor:
Faria, Fatema Tuj Johora, Moin, Mukaffi Bin, Rahman, Md. Mahfuzur, Shanto, Md Morshed Alam, Fahim, Asif Iftekher, Hoque, Md. Moinul
With the increasing popularity of daily information sharing and acquisition on the Internet, this paper introduces an innovative approach for intent classification in Bangla language, focusing on social media posts where individuals share their thoug
Externí odkaz:
http://arxiv.org/abs/2409.09504
This study evaluates the application of large language models (LLMs) for intent classification within a chatbot with predetermined responses designed for banking industry websites. Specifically, the research examines the effectiveness of fine-tuning
Externí odkaz:
http://arxiv.org/abs/2410.04925
Classification is a core NLP task architecture with many potential applications. While large language models (LLMs) have brought substantial advancements in text generation, their potential for enhancing classification tasks remains underexplored. To
Externí odkaz:
http://arxiv.org/abs/2410.02028
Autor:
KULIGOWSKA, Karolina1 kkuligowska@wne.uw.edu.pl, KOWALCZUK, Bartłomiej2 b.kowalczuk@tidio.net
Publikováno v:
Journal of Applied Economic Sciences. Fall2024, Vol. 19 Issue 3, p317-325. 9p.
