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pro vyhledávání: '"slot filling"'
Zero-shot slot filling is a well-established subtask of Natural Language Understanding (NLU). However, most existing methods primarily focus on single-turn text data, overlooking the unique complexities of conversational dialogue. Conversational data
Externí odkaz:
http://arxiv.org/abs/2411.18980
Autor:
Bhargav, G P Shrivatsa, Neelam, Sumit, Sharma, Udit, Ikbal, Shajith, Sreedhar, Dheeraj, Karanam, Hima, Joshi, Sachindra, Dhoolia, Pankaj, Garg, Dinesh, Croutwater, Kyle, Qi, Haode, Wayne, Eric, Murdock, J William
We present an approach to build Large Language Model (LLM) based slot-filling system to perform Dialogue State Tracking in conversational assistants serving across a wide variety of industry-grade applications. Key requirements of this system include
Externí odkaz:
http://arxiv.org/abs/2406.08848
Publikováno v:
Transactions of the Chinese Society of Agricultural Engineering. Jul2024, Vol. 40 Issue 13, p156-162. 7p.
Autor:
Zhu, Meng, Xu, Xiaolong
Publikováno v:
Data Technologies and Applications, 2024, Vol. 58, Issue 4, pp. 590-607.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/DTA-03-2023-0088
Autor:
Robbani, Irfan, Reisert, Paul, Inoue, Naoya, Pothong, Surawat, Guerraoui, Camélia, Wang, Wenzhi, Naito, Shoichi, Choi, Jungmin, Inui, Kentaro
Prior research in computational argumentation has mainly focused on scoring the quality of arguments, with less attention on explicating logical errors. In this work, we introduce four sets of explainable templates for common informal logical fallaci
Externí odkaz:
http://arxiv.org/abs/2406.12402
Akademický článek
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Autor:
Zhao, Jinxu, Dong, Guanting, Qiu, Yueyan, Hui, Tingfeng, Song, Xiaoshuai, Guo, Daichi, Xu, Weiran
In a realistic dialogue system, the input information from users is often subject to various types of input perturbations, which affects the slot-filling task. Although rule-based data augmentation methods have achieved satisfactory results, they fai
Externí odkaz:
http://arxiv.org/abs/2402.14494
Publikováno v:
PeerJ Computer Science, Vol 10, p e2346 (2024)
Understanding spoken language is crucial for conversational agents, with intent detection and slot filling being the primary tasks in natural language understanding (NLU). Enhancing the NLU tasks can lead to an accurate and efficient virtual assistan
Externí odkaz:
https://doaj.org/article/d44aa6ca1a0a46bd970abcb7d1e715c5
Akademický článek
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Autor:
Pham, Thinh, Nguyen, Dat Quoc
Profile-based intent detection and slot filling are important tasks aimed at reducing the ambiguity in user utterances by leveraging user-specific supporting profile information. However, research in these two tasks has not been extensively explored.
Externí odkaz:
http://arxiv.org/abs/2312.08737