群岛
发表于 2025-3-23 10:37:17
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Substitution
发表于 2025-3-23 14:19:59
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EVEN
发表于 2025-3-23 21:29:36
Alexander Christiani French as an inflected language, b) optimizes the estimation of probabilities, c) allows the user flexibility in choosing a tagset. The problem in extracting lexical probabilities from a limited training corpus is that the statistical model may not necessarily represent the use of a particular word
Exploit
发表于 2025-3-23 22:11:19
Alexander Christianier. The task of question generation (QG) is to generate a corresponding natural language question given the input answer, while question answering (QA) is a reverse task to find a proper answer given the question. For the KBQA task, the answer could be regarded as a fact containing a predicate and t
Immunization
发表于 2025-3-24 03:18:39
Alexander Christianiularly in the biomedical field. On biomedical CQA platforms, patients share information about diseases, drugs and symptoms by communicating with each other. Therefore, the biomedical CQA platforms become particularly valuable resources for information and knowledge acquisition of patients. To accura
持续
发表于 2025-3-24 06:51:51
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碌碌之人
发表于 2025-3-24 11:17:07
Alexander Christianialogue system, especially speaker state closely related to emotion. Because of the increasing speakers, it is more challenging to model speakers’ state in multi-speaker conversation than in two-speaker conversation. In this paper, we focus on emotion detection in multi-speaker conversation–a more ge
chastise
发表于 2025-3-24 16:10:02
Alexander Christianiis usually a practical and effective solution, especially for some complicated questions (e.g., How and Why). Recent years have witnessed the great successes of knowledge graphs (KGs) in KBQA systems, while there are still few works focusing on making full use of KGs in FAQ-based QA. In this paper,
conquer
发表于 2025-3-24 22:27:54
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intertwine
发表于 2025-3-25 01:56:34
Alexander Christianiis usually a practical and effective solution, especially for some complicated questions (e.g., How and Why). Recent years have witnessed the great successes of knowledge graphs (KGs) in KBQA systems, while there are still few works focusing on making full use of KGs in FAQ-based QA. In this paper,